Luleå University of Technology Publications
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Ecohydraulic approach for ecological measures in regulated rivers
No full textHydropower is an energy source that is currently considered to be both climate- and environmentally friendly. It is utilized on both large and small scales and has a low carbon footprint, which has led to increased attention in recent years. The growing influence of renewable energy sources such as solar and wind power has also brought the regulatory capabilities of hydropower within electrical grids into focus. Despite the significant climate benefits of hydropower, there remain substantial challenges in adapting it to minimize environmental impacts. The latest European water framework has highlighted how fish and other aquatic organisms are harmed by limitations on upstream and downstream migration caused by hydropower plants. Given the importance of maximizing hydropower electricity production while minimizing environmental impacts, there is a need for more knowledge regarding how mitigation measures for aquatic organisms can be implemented. By combining knowledge of water flow patterns in hydropower areas with insights into the behavior of fish species in these environments, it is possible to facilitate migration both upstream and downstream while ensuring optimal use of hydropower. The first section focuses on downstream migrating salmon smolts. In this study, telemetry data from tagged smolts were analyzed alongside a 3D flow model of an area in northern Sweden where a large hydropower plant affects one of the largest rivers for salmon reproduction. The study shows that the smolts follow the main channel and are influenced by the flow rate. Higher flow velocities tend to cause the smolts to concentrate more in the main channel, while lower flows result in a broader distribution across the riverbed. The smolts are also partially influenced by the boom installed to direct the flow towards the fish pass. The second work section addresses how climate change may impact extreme flow events in a dammed river in northern Sweden. With anticipated climate change, more significant variation in precipitation is expected to affect the northern hemisphere, resulting in altered flow conditions. By studying historical data, an extreme flow event was identified and modeled using a 2D model. Flow variations were analyzed in relation to the preferred flow conditions for grayling. The study demonstrates that grayling are sensitive to large flow variations in the area. The most significant impact occurs when an extreme flow coincides with their spawning period. As the area is heavily regulated with hydropower plants placed closely together, downstream plants have a significant impact on water levels upstream. The area is particularly sensitive if water levels are rapidly lowered, as this can lead to stranding. This study combines various methods to investigate flow and flow variations, utilizing both detailed 3D models and broader 2D models. It demonstrates the potential for flow models to interact with ecological studies to deepen our understanding of the ecological state of rivers affected by hydropower development. This is a broad field with significant knowledge gaps, and it is hoped that further studies will be conducted in the future
Enhancing railway infrastructure monitoring with AI: A machine learning approach for event detection
No full textThis study presents a machine learning-based framework for detecting critical events in railway infrastructure by analyzing vibration signals from trackside accelerometers. Traditional maintenance is often reactive and labor-intensive, but this approach uses continuous sensing and data analytics to enable proactive, real-time monitoring. The research leverages a comprehensive pipeline that includes data preprocessing, segmentation of time-series data into one-second intervals labeled as "event" or "no-event", and the extraction of statistical, temporal, and spectral features like crest factor and kurtosis. Key contribution of this work is the systematic evaluation of 72 algorithm-feature selection configurations. Twelve diverse classification algorithms were compared, including tree-based, linear, and neural network models. Extensive hyperparameter optimization was performed to benchmark performance using metrics such as accuracy, precision, recall, and F1-score. The Multi-Layer Perceptron (MLPClassifier) achieved a peak cross-validation accuracy of 98.89% with the full feature set. The study also found that comparable accuracy (98.67%) could be achieved with a 47% dimensionality reduction using Recursive Feature Elimination (RFE) with only eight features, demonstrating a balance between efficiency and performance. The findings provide actionable insights for developing scalable, high-performance event detection systems.Full text license: CC BY 4.0;</p
Acute stress is associated with increased auditory distraction: evidence from a cross-modal oddball task
No full textAttentional Control Theory suggests that acute stress reduces the efficiency of working memory and top-down control, increasing susceptibility to distraction. In contrast, Cognitive Reallocation accounts suggest that acute stress narrows attentional focus and potentially reduces distraction. We tested these competing predictions using a cross-modal oddball task, comparing participants exposed to an acute stressor, via a realistic firefighter training exercise, with an unstressed control group. Participants categorised visual targets preceded by either a standard sound or a rare deviant (a noise burst or a semantically congruent or incongruent word). Both groups were distracted by the deviant sounds, but the effect was larger in those exposed to the stressor, particularly early in the session. Over time, this difference diminished—consistent with recovery from stress exposure and stronger habituation in controls. These results indicate that acute stress is associated with heightened vulnerability to auditory distraction in a pattern resembling reduced working memory availability.Full text license: CC BY 4.0;Funder: Fundação Bial (grant No. 201/20);Related dataset: 10.17030/uclan.data.00000603</p
Coupled numerical modelling of high-voltage electric pulse (HVEP) rock fracturing using COMSOL and 4D-LSM
No full textHigh-voltage electric pulse (HVEP) rock fragmentation has demonstrated substantial potential for sustainable fracturing of hard rocks owing to its energy efficiency. The transient nature and highly disruptive characteristics of its physical fracturing process render experimental investigation of the underlying rock-breaking mechanisms challenging. However, existing numerical studies lack comprehensive models that precisely link electrical breakdown phenomena with mechanical disintegration processes. This study combines COMSOL electrical breakdown simulations with four-dimension lattice spring model (4D-LSM) mechanical analysis to establish a coupled HVEP rock fragmentation model. The core concept of the model construction is to import the temperature field of the plasma channel obtained from the electrical breakdown into the mechanical solver to realize the precise connection between the two stages. The validated numerical model elucidates the full process of HVEP-induced fragmentation under varying electrical parameters. Furthermore, the effects of confining pressure and mineral grain size on fragmentation behavior have been investigated. Finally, parametric simulations across 25 electrical parameter combinations demonstrate the critical role of electrode spacing optimization in achieving energy-efficient rock fragmentation. These findings provide a predictive tool for designing efficient HVEP systems in deep resource extraction and mineral processing engineering.Funder: National Natural Science Foundation of China (52209144, 12472405);Full text license: CC BY-NC-ND</p
Triboelectric Nanogenerators for Future Space Missions
No full textSpace exploration is significant for scientific innovation, resource utilization, and planetary security. Space exploration involves several systems including satellites, space suits, communication systems, and robotics, which have to function under harsh space conditions such as extreme temperatures (− 270 to 1650 °C), microgravity (10⁻⁶ g), unhealthy humidity (< 20% RH or > 60% RH), high atmospheric pressure (~ 1450 psi), and radiation (4000–5000 mSv). Conventional energy-harvesting technologies (solar cells, fuel cells, and nuclear energy), that are normally used to power these space systems have certain limitations (e.g., sunlight dependence, weight, degradation, big size, high cost, low capacity, radioactivity, complexity, and low efficiency). The constraints in conventional energy resources have made it imperative to look for non-conventional yet efficient alternatives. A great potential for enhancing efficiency, sustainability, and mission duration in space exploration can be offered by integrating triboelectric nanogenerators (TENGs) with existing energy sources. Recently, the potential of TENG including energy harvesting (from vibrations/movements in satellites and spacecraft), self-powered sensing, and microgravity, for multiple applications in different space missions has been discussed. This review comprehensively covers the use of TENGs for various space applications, such as planetary exploration missions (Mars environment monitoring), manned space equipment, In-orbit robotic operations /collision monitoring, spacecraft's design and structural health monitoring, Aeronautical systems, and conventional energy harvesting (solar and nuclear). This review also discusses the use of self-powered TENG sensors for deep space object perception. At the same time, this review compares TENGs with conventional energy harvesting technologies for space systems. Lastly, this review talks about energy harvesting in satellites, TENG-based satellite communication systems, and future practical implementation challenges (with possible solutions).Full text: CC BY license;</p
Effects of the Invasive Round Goby on Swedish Recreational Fishing Values
No full textThe round goby, an invasive fish from the Black and Caspian Seas, has spread to Swedish waters, threatening recreational fisheries. We modeled impacts on the future recreational fishery in Sweden using data from a recreational fishing survey, and estimated effects of the round goby on other fish species. Values attached to recreational fishing were estimated using a travel cost approach. Catch and consumer surplus were compared before and after a 10-year increase in round goby abundance. Overall impacts of a 10-year increase in round goby abundance in Swedish waters would reduce the present value of consumer surplus by SEK 379-million (EUR 33-million). Any management action keeping a status quo in round goby impact with a price less than about 3 million EUR yearly would hence be justified. This study highlights how aquatic invasive species can cause substantial social losses and that proactive management may be cost-efficient.Full text license: CC BY-NC-ND 4.0;</p
Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformer
No full textThe impressive advancements in semi-supervised learning have driven researchers to explore its potential in object detection tasks within the field of computer vision. Semi-Supervised Object Detection (SSOD) leverages a combination of a small labeled dataset and a larger, unlabeled dataset. This approach effectively reduces the dependence on large labeled datasets, which are often expensive and time-consuming to obtain. Initially, SSOD models encountered challenges in effectively leveraging unlabeled data and managing noise in generated pseudo-labels for unlabeled data. However, numerous recent advancements have addressed these issues, resulting in substantial improvements in SSOD performance. This paper presents a comprehensive review of 28 cutting-edge developments in SSOD methodologies, from Convolutional Neural Networks (CNNs) to Transformers. We delve into the core components of semi-supervised learning and its integration into object detection frameworks, covering data augmentation techniques, pseudo-labeling strategies, consistency regularization, and adversarial training methods. Furthermore, we conduct a comparative analysis of various SSOD models, evaluating their performance and architectural differences. We aim to ignite further research interest in overcoming existing challenges and exploring new directions in semi-supervised learning for object detection.Full text license: CC BY 4.0;Funder: AIRISE (101092312)</p
Use of Alternative and Augmentative Communication (AAC) in Preschool
No full textSyftet med denna studie är att beskriva hur förskollärare använder alternativ och kompletterande kommunikation (AKK) för att stödja kommunikationen både med barn i behov av språkligt stöd och de som inte har behov. Studien utgår från två forskningsfrågor: I vilka situationer kan AKK behövas för att underlätta kommunikationen? Vilka erfarenheter har förskolärararen av användning av AKK i verksamheten? Det sociokulturella perspektivet används som teoretisk utgångspunkt och fenomenografisk analysmetod ligger som grund för analysen. Metoden är kvalitativ och datainsamlingen har genomförts genom semistrukturerade intervjuer med fyra förskollärare. Resultatet visar att AKK, främst i form av tecken som AKK (TAKK) och visuellt stöd används i vardagliga såsom måltider, samlingar, övergångar, fri lek och i känsloladdade situationer. Förskollärarna beskriver användningen av AKK ökar barns förståelse, delaktighet och möjlighet att uttrycka sig. Erfarenheterna visar att användningen påverkas av pedagogers utbildning, trygghet och gemensamma arbetssätt. Slutsatsen är att AKK har stor potential som inkluderande verktyg i förskolan, men för att uppnå en viss likvärdighet krävs kompetensutveckling, tydliga riktlinjer och ett gemensamt förhållningsätt i arbetslaget
Enhancing Oxidation and Energy Utilisation by Controlling O2 and Gas Flow in Magnetite Pellet-Bed Induration
No full textAs Sweden transitions to hydrogen-based steel production, excess O2 generated as a byproduct of H2 production through water electrolysis is likely to be available. This presents an opportunity to use extra O2 for reducing fuel consumption during production of iron ore pellets. Considerable heat is released as magnetite is oxidised to hematite during induration. Increased O2 content in the process gas is expected to accelerate the exothermic oxidation reaction, allowing faster intrinsic heating of the bed. This study examines various energy scenarios utilising O2-enriched gas (40 vol% O2) relative to a base case that uses low-O2 gas (13 vol% O2). The focus is the effects of the flow rates and O2 contents in the inflow gas on the temperature development and physicochemical properties (oxidation degree and cold compression strength) of pellets across a 100-kg pot furnace bed. Enriching the inflow gas with O2 has advantages with regard to the aforementioned properties. Notably, utilising O2-enriched gas at a reduced flow rate (in this case, 30% less gas volume compared with the base case) enables improved heat distribution relative to the base case with low-O2 gas. In addition to the effects on the energy and pellet properties, the microstructures are analysed with respect to the underlying oxidation mechanisms.Full text: CC BY-NC-ND license;For funding information, see: https://doi.org/10.2355/isijinternational.ISIJINT-2025-130</p
The Association Between Psychological Well-Beingand Resistance Training: A Survey Study
No full textIntroduktion:Psykiskt välbefinnande är en stor del av våran hälsa. Detta kan påverkas avolika faktorer såsom fysisk aktivitet. Tidigare studier har visat på att både konditions- ochstyrketräning har gett goda effekter på måendet. Studier som undersökt sambandet mellankonditionsträning och psykiskt välbefinnande är mer omfattande medan studierna på de somstyrketränar är mer inriktade mot personer som redan har en klinisk diagnostisera psykiskohälsa. Syfte: Syftet var att kartlägga psykiskt välbefinnande hos vuxna som styrketränar regelbundetjämfört med vuxna som inte tränar alls, varken styrketräning eller annan fysisk aktivitet. Metod: Studien genomfördes som en tvärsnittsstudie med enkät som datainsamlingsmetod. Totalt inkluderades 57 deltagare som bodde i Norrbotten. Enkäten bestod avegenkonstruerade frågor om träningsvanor samt ett validerat frågeformulär General HealthQuestionnaire-12 (GHQ-12) för att mäta psykisk ohälsa. Data analyserades med deskriptivstatistik, Student’s t-test samt Pearsons korrelationstest. Resultat: Resultatet visade att personer som styrketränar regelbundet rapporterade högreupplevd psykiskt välbefinnande och mindre förekomst av symptom på psykisk ohälsa jämförtmed personer som inte tränar. Skillnaden mellan grupperna var statistiskt signifikant. Däremot påvisades inget signifikant samband mellan träningsfrekvens och nivå av psykisktvälbefinnande bland de styrketränande deltagarna. Konklusion: Studien antyder att styrketräning är associerad med bättre psykisktvälbefinnande hos vuxna, oberoende av träningsfrekvens. Styrketräning kan därmed vara enrelevant hälsofrämjande och fysioterapeutisk insats för att stödja både psykisk och fysiskhälsa. Det krävs dock ytterligare studier med ett annat upplägg för att kunna fastställakausaliteten