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  • 1.
    Stathoulopoulos, Nikolaos
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Koval, Anton
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Nikolakopoulos, George
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    3DEG: Data-Driven Descriptor Extraction for Global re-localization in subterranean environments2024In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 237, no part B, article id 121508Article in journal (Refereed)
    Abstract [en]

    Localization algorithms that rely on 3D LiDAR scanners often encounter temporary failures due to various factors, such as sensor faults, dust particles, or drifting. These failures can result in a misalignment between the robot’s estimated pose and its actual position in the global map. To address this issue, the process of global re-localization becomes essential, as it involves accurately estimating the robot’s current pose within the given map. In this article, we propose a novel global re-localization framework that addresses the limitations of current algorithms heavily reliant on scan matching and direct point cloud feature extraction. Unlike most methods, our framework eliminates the need for an initial guess and provides multiple top-� candidates for selection, enhancing robustness and flexibility. Furthermore, we introduce an event-based re-localization trigger module, enabling autonomous robotic missions. Focusing on subterranean environments with low features, we leverage range image descriptors derived from 3D LiDAR scans to preserve depth information. Our approach enhances a state-of-the-art data-driven descriptor extraction framework for place recognition and orientation regression by incorporating a junction detection module that utilizes the descriptors for classification purposes. The effectiveness of the proposed approach was evaluated across three distinct real-life subterranean environments.

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  • 2.
    Stathoulopoulos, Nikolaos
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Koval, Anton
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Nikolakopoulos, George
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    A Comparative Field Study of Global Pose Estimation Algorithms in Subterranean Environments2024In: International Journal of Control, Automation and Systems, ISSN 1598-6446, E-ISSN 2005-4092, Vol. 22, no 2, p. 690-704Article in journal (Refereed)
  • 3.
    Venkatesh, Naveen
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. School of Mechanical Engineering (SMEC), Vellore Institute of Technology, Chennai, India.
    Sugumaran, V.
    School of Mechanical Engineering (SMEC), Vellore Institute of Technology, Chennai, India.
    Subramanian, Balaji
    Department of Mechanical Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, 603203 Chennai, India.
    Josephin, J.S. Femilda
    Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Istinye University, Istanbul, Turkiye; Department of Autotronics, Institute of Automobile Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, Tamil Nadu, India.
    Varuvel, Edwin Geo
    Department of Mechanical Engineering, Faculty of Engineering and Natural Sciences, Istinye University, Istanbul, Turkiye.
    A comparative study on bayes classifier for detecting photovoltaic module visual faults using deep learning features2024In: Sustainable Energy Technologies and Assessments, ISSN 2213-1388, E-ISSN 2213-1396, Vol. 64, article id 103713Article in journal (Refereed)
    Abstract [en]

    Renewable energy is found to be an effective alternative in the field of power production owing to the recent energy crises. Among the available renewable energy sources, solar energy is considered the front runner due to its ability to deliver clean energy, free availability and reduced cost. Photovoltaic (PV) modules are placed over large geographical regions for efficient solar energy harvesting, making it difficult to carry out maintenance and restoration works. Thermal stresses inherited by photovoltaic modules (PVM) under varying environmental conditions can lead to failure of internal components. Such failures when left undetected impart a number of complications in the system that will lead to unsafe operation and seizure. To avoid the aforementioned uncertainties, frequent monitoring of PVM is found necessary. The fault identification in PVM using essential features taken from aerial images is presented in this study. The feature extraction procedure was carried out using convolutional neural networks (CNN), while the feature selection process was carried out by the J48 decision tree method. Six test conditions were considered such as delamination, glass breakage, discoloration, burn marks, snail trail, and good panel. Bayes Net (BN) and Naïve Bayes (NB) classifiers were utilized as primary classifiers for all the test conditions. Results obtained from the classifiers were compared and the best classifier for fault detection in PVM is suggested.

    The full text will be freely available from 2027-03-02 17:59
  • 4.
    Sharma, Pratibha
    et al.
    Human Behaviour Department, Institute of Human Behaviour and Allied Sciences, Dilshad Garden, New Delhi, India; Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India.
    Roy, Ambuj
    Department of Cardiology, All India Institute of Medical Sciences, New Delhi, India.
    Dhamija, Rajinder K.
    Human Behaviour Department, Institute of Human Behaviour and Allied Sciences, Dilshad Garden, New Delhi, India.
    Bhushan, Sudha
    Department of Cardiology, All India Institute of Medical Sciences, New Delhi, India.
    Baswal, Kamal
    Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India.
    Kulandaisamy, Rajkumar
    Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India.
    Yadav, Satyavir
    Department of Cardiology, All India Institute of Medical Sciences, New Delhi, India.
    Kumar, Saroj
    Luleå University of Technology, Department of Health, Learning and Technology, Nursing and Medical Technology. Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India.
    Inampudi, Krishna Kishore
    Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India.
    A comprehensive proteomic profiling of urinary exosomes and the identification of early non-invasive biomarker in patients with coronary artery disease2024In: Journal of Proteomics, ISSN 1874-3919, E-ISSN 1876-7737, Vol. 293, article id 105059Article in journal (Refereed)
  • 5.
    Sharma, Gaurav
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Samuelson, Olle
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Industrilized and sustainable construction.
    Simu, Kajsa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Industrilized and sustainable construction.
    A Conceptual Model for AI-Enabled Digitalization of Construction Site Management Decision Making2024In: International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024, p. 145-149Conference paper (Other academic)
  • 6.
    Elragal, Ahmed
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Elgendy, Nada
    M3S, Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland.
    A Data-Driven Decision-Making Readiness Assessment Model: The Case of a Swedish Food Manufacturer2024In: Decision Analytics Journal, ISSN 2772-6622, Vol. 10, article id 100405Article in journal (Refereed)
    Abstract [en]

    This study proposes a model to assess data-driven decision-making (DDDM) readiness in organizations. We present the results from investigating the DDDM readiness of a Swedish organization in the food industry. We designed and developed a questionnaire to collect data about the organization’s decision-making and IT systems. We conducted eleven interviews at the case study organization: ten with various functional decision-makers and one with the IT Manager about IT systems. The interview data were then analyzed against known decision theories and state-of-the-art DDDM. Based on the interview outcomes, we analyze the data according to the assessment model and recommend changes to the organization’s readiness for data-driven decisions. The findings show that while the organization was assessed as ready in the decision-making process and decision-maker pillars, it was not ready in the data or analytics pillars. Accordingly, we recommend a set of actions, including considering integration and decision systems, further developing dashboards, increasing data and analytics resources (such as enterprise data warehouse, big data management tools, data lake environment, and data analytics algorithms), and defining key roles necessary for digitalization and DDDM (such as Data Engineer, Data Scientist, Business Intelligence Specialist, Chief Data Officer, and Data Warehouse Designer/Administrator). The contribution of this study is the DDDM readiness assessment model, accompanied by a questionnaire for determining the readiness level in organizations.

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  • 7.
    Souza Rossi, Henrique
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Åhlund, Christer
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Cotanis, Irina
    Infovista AB, Sweden.
    A Demonstration of ALTRUIST for Conducting QoE Subjective Tests in Immersive Systems2024In: 2024 IEEE 21st Consumer Communications & Networking Conference (CCNC), IEEE, 2024, p. 1120-1121Conference paper (Refereed)
  • 8.
    Min, Xinzhe
    et al.
    School of Civil Engineering and Architecture, Nanjing Institute of Technology, Nanjing, China.
    Zhang, Jiwen
    Key Laboratory of Concrete and Prestressed Concrete Structures of Ministry of Education, National Engineering Research Center for Prestressing Technology, School of Civil Engineering, Southeast University, 211189, Nanjing, China.
    Tu, Yongming
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering. Key Laboratory of Concrete and Prestressed Concrete Structures of Ministry of Education, National Engineering Research Center for Prestressing Technology, School of Civil Engineering, Southeast University, 211189, Nanjing, China.
    Li, Xing
    Key Laboratory of Concrete and Prestressed Concrete Structures of Ministry of Education, National Engineering Research Center for Prestressing Technology, School of Civil Engineering, Southeast University, 211189, Nanjing, China.
    Wang, Chao
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.
    Sas, Gabriel
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.
    Elfgren, Lennart
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.
    A full-range fatigue life prediction model for RC beams strengthened with prestressed CFRP plates accounting for the impact of FRP debonding2024In: Engineering structures, ISSN 0141-0296, E-ISSN 1873-7323, Vol. 301, article id 117305Article in journal (Refereed)
  • 9.
    Simonsson, Johan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Optimation AB, Uppsala, Sweden.
    Atta, Khalid Tourkey
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Birk, Wolfgang
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    A Graph Theoretical Approach to Modeling of District Energy Networks2024In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865Article in journal (Refereed)
    Abstract [en]

    Simulation of thermal dynamics in city-scale district energy grids often becomes computationally prohibitive for long simulation runs. Most current model order reduction methods offer limited interpretability with regards to the nonreduced system and are not in general applicable for varying flow rates, multiple producers, or changing flow directions. This article presents a graph perspective on modeling of district energy networks. Based on spectral graph theory, a novel method for model order reduction of district energy systems is proposed. The method approximates the solution of an optimization problem, minimizing the coefficients of the local truncation error for the advection equation. Furthermore, a method for calculating the intracluster temperature distribution is presented. It is shown that the method can be used to reduce the thermal dynamic model of a city-scale energy grid, resulting in a coarser temporal and spatial resolution, with a significant decrease in simulation time. The relative root-mean-square error (rRMSE) was 2.5% for the temperature in the evaluation scenario, comparing the reduced-order system with the nonreduced system at the instances of the coarser time step.

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  • 10.
    Tadaros, Marduch
    et al.
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. Linköping University, Department of Science and Technology, Norrköping, Sweden.
    Kyriakakis, Nikolaos A.
    Technical University of Crete, School of Production Engineering and Management, University Campus, Chania, 73100, Greece.
    A Hybrid Clustered Ant Colony Optimization Approach for the Hierarchical Multi-Switch Multi-Echelon Vehicle Routing Problem with Service Times2024In: Computers & industrial engineering, ISSN 0360-8352, E-ISSN 1879-0550, no 190, article id 110040Article in journal (Refereed)
    Abstract [en]

    In this paper, the Hierarchical Multi Switch Multi Echelon Vehicle Routing Problem with Service Times (HMSME-VRP-ST) is presented. This novel problem considers distribution applications in which goods are delivered either directly from a central depot or through intermediate facilities called switch points. Commodities are loaded into interchangeable containers called swap bodies at the central depot, and can be transferred from one vehicle to another at the switch points. The goal is to minimize fixed and variable costs of the vehicle fleet and swap-bodies while serving a predetermined set of customers. The routes are constrained by time and swap bodies by loading capacity. A mathematical model of the HMSME-VRP-ST is presented, and a Hybrid Clustered Ant Colony Optimization (HCACO) algorithm is proposed to address the complexity of the problem. The approach utilizes the ant-based clustering algorithm, combining the density and connectivity properties of clustering for creating promising neighborhoods with the solution construction methodology and pheromone-based memory of the Ant Colony Optimization framework. Additionally, two local search schemes based on Variable Neighborhood Descent are incorporated to further improve the generated solutions. The behavior of each HCACO variant is analyzed, and their results are compared to a Greedy Randomized Adaptive Search Procedure metaheuristic in 36 newly generated benchmarks comprising of clustered, uniformly random, and mixed clustered-random instances.

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  • 11.
    Vega-Mendoza, Mariana
    et al.
    Luleå University of Technology, Department of Health, Education and Technology, Health, Medicine and Rehabilitation.
    Eriksson Sörman, Daniel
    Luleå University of Technology, Department of Health, Education and Technology, Health, Medicine and Rehabilitation.
    Josefsson, Maria
    Umeå School of Business, Economics and Statistics (USBE), Sweden.
    Körning Ljungberg, Jessica
    Luleå University of Technology, Department of Health, Education and Technology, Health, Medicine and Rehabilitation.
    A longitudinal study of episodic memory recall in multilinguals2024In: International Journal of Bilingualism, ISSN 1367-0069, E-ISSN 1756-6878, Vol. 28, no 1, p. 125-145Article in journal (Refereed)
    Abstract [en]

    Aim: This study investigates the effects of degree of multilingualism on cognitive functions in adulthood, with focus on episodic memory recall and including measures of verbal fluency as well as global cognition.

    Design: We studied a large population-based cohort cross-sectionally, and we also assessed changes over time through longitudinal measurements on four time-points over a 15 year period. Participants were drawn from the Betula prospective cohort study in Umeå, Sweden. The participants included in this study at baseline (n = 894, mean age = 51.44, 59.4% females) were divided according to number of languages into bilinguals (n = 395), trilinguals (n = 284), quadrilinguals (n = 169), and pentalinguals (n = 46).

    Data and analysis: We analysed performance on tasks of episodic memory recall, verbal fluency (letter and category) and global cognition (Minimental State Examination, MMSE) both cross-sectionally and longitudinally. The control background variables were baseline age, gender, years of education, general fluid ability Gf (Wechsler Block Design Test), and socioeconomic status. We employed a linear mixed modelling approach with entropy balancing weights to assess effects of degree of multilingualism on cognitive functions.

    Findings and conclusions: Using bilinguals as the reference group, our results indicated that all the other multilingual groups exhibited superior performance on episodic memory recall than bilinguals at baseline. The rate of change over time did not differ for trilinguals and pentalinguals compared to bilinguals. While quadrilinguals declined more over time than bilinguals, they still scored significantly higher than bilinguals at the last test wave. For letter fluency, similarly, all language groups scored higher than bilinguals at baseline, and none of the groups differed from bilinguals in rate of change over time. With regard to category fluency, quadrilinguals scored higher than bilinguals at baseline, but trilinguals and pentalinguals did not differ from bilinguals and none of the groups differed in change over time compared to bilinguals. Finally, for global cognition (MMSE), trilinguals and quadrilinguals scored significantly higher than bilinguals at baseline with no differences in change over time for any of the groups relative to bilinguals. Our study contributes to the understanding of multilingual cognition and sheds light into an under-researched cognitive domain known to decline in normal ageing, namely episodic memory recall.

    Significance: Our study emphasizes the importance of researching less explored aspects of multilingualism on cognition, in particular on episodic memory recall, to aid our understanding of factors that could potentially aid cognitive decline in later adulthood.

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  • 12.
    Barbera, Mariagnese
    et al.
    Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Yliopistonranta 1C, 70211, Kuopio, Finland; The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan’s Road, LondonLondon, W6 8RP, UK.
    Lehtisalo, Jenni
    Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Yliopistonranta 1C, 70211, Kuopio, Finland; Population Health Unit, Finnish Institute for Health and Welfare, Mannerheimintie 166, P.O. Box 30, Helsinki, Finland.
    Perera, Dinithi
    The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan’s Road, London, W6 8RP, UK; FINGERS Brain Health Institute, C/O Stockholms Sjukhem, Box 122 30, SE-102 26, Stockholm, Sweden.
    Aspö, Malin
    Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Karolinska Vägen 37A, 171 64, Solna, Sweden; Theme Inflammation and Aging, Medical Unit Aging, Karolinska University Hospital, Karolinska Vägen 37A, 171 76, Solna, Sweden.
    Cross, Mary
    Imperial Clinical Trials Unit, School of Public Health, Faculty of Medicine, Imperial College London, Imperial College London, Stadium House, 68 Wood Lane, London, W12 7RH, UK.
    De Jager Loots, Celeste A.
    The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan’s Road, LondonLondon, W6 8RP, UK.
    Falaschetti, Emanuela
    Imperial Clinical Trials Unit, School of Public Health, Faculty of Medicine, Imperial College London, Imperial College London, Stadium House, 68 Wood Lane, London, W12 7RH, UK.
    Friel, Naomi
    The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan’s Road, LondonLondon, W6 8RP, UK.
    Luchsinger, José A.
    Departments of Medicine and Epidemiology, Columbia University Irving Medical Center, 622 W 168Th St, New York, NY, USA.
    Gavelin, Hanna Malmberg
    Department of Psychology, Umeå University, 901 87, Umeå, Sweden.
    Peltonen, Markku
    Population Health Unit, Finnish Institute for Health and Welfare, Mannerheimintie 166, P.O. Box 30, Helsinki, Finland; FINGERS Brain Health Institute, C/O Stockholms Sjukhem, Box 122 30, SE-102 26, Stockholm, Sweden.
    Price, Geraint
    The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan’s Road, LondonLondon, W6 8RP, UK.
    Stigsdotter Neely, Anna
    Luleå University of Technology, Department of Health, Education and Technology, Health, Medicine and Rehabilitation. Department of Social and Psychological Studies, Karlstad University, 651 88, Karlstad, Sweden.
    Thunborg, Charlotta
    Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Karolinska Vägen 37A, 171 64, Solna, Sweden; Theme Inflammation and Aging, Medical Unit Aging, Karolinska University Hospital, Karolinska Vägen 37A, 171 76, Solna, Sweden.
    Tuomilehto, Jaakko
    Population Health Unit, Finnish Institute for Health and Welfare, Mannerheimintie 166, P.O. Box 30, Helsinki, Finland; Department of Public Health, University of Helsinki, PO BOX 20, 00014, Helsinki, Finland; Diabetes Research Group, King Abdulaziz University, 21589, Jeddah, Saudi Arabia.
    Mangialasche, Francesca
    FINGERS Brain Health Institute, C/O Stockholms Sjukhem, Box 122 30, SE-102 26, Stockholm, Sweden; Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Karolinska Vägen 37A, 171 64, Solna, Sweden; Theme Inflammation and Aging, Medical Unit Aging, Karolinska University Hospital, Karolinska Vägen 37A, 171 76, Solna, Sweden.
    Middleton, Lefkos
    The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan’s Road, LondonLondon, W6 8RP, UK; Directorate of Public Health, Imperial College NHS Healthcare Trust Hospitals, Praed Street, London, W2 1NY, UK.
    Ngandu, Tiia
    Population Health Unit, Finnish Institute for Health and Welfare, Mannerheimintie 166, P.O. Box 30, Helsinki, Finland; Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Karolinska Vägen 37A, 171 64, Solna, Sweden.
    Solomon, Alina
    Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Yliopistonranta 1C, 70211, Kuopio, Finland; The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan’s Road, London, W6 8RP, UK; Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Karolinska Vägen 37A, 171 64, Solna, Sweden.
    Kivipelto, Miia
    The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan’s Road, LondonLondon, W6 8RP, UK; Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Karolinska Vägen 37A, 171 64, Solna, Sweden; Theme Inflammation and Aging, Medical Unit Aging, Karolinska University Hospital, Karolinska Vägen 37A, 171 76, Solna, Sweden; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Yliopistonranta 1C, 70211, Kuopio, Finland.
    A multimodal precision-prevention approach combining lifestyle intervention with metformin repurposing to prevent cognitive impairment and disability: the MET-FINGER randomised controlled trial protocol2024In: Alzheimer's Research & Therapy, E-ISSN 1758-9193, Vol. 16, no 1, article id 23Article in journal (Refereed)
    Abstract [en]

    Background: Combining multimodal lifestyle interventions and disease-modifying drugs (novel or repurposed) could provide novel precision approaches to prevent cognitive impairment. Metformin is a promising candidate in view of the well-established link between type 2 diabetes (T2D) and Alzheimer’s Disease and emerging evidence of its potential neuro-protective effects (e.g. vascular, metabolic, anti-senescence). MET-FINGER aims to test a FINGER 2.0 multimodal intervention, combining an updated FINGER multidomain lifestyle intervention with metformin, where appropriate, in an APOE ε4-enriched population of older adults (60–79 years) at increased risk of dementia. Methods: MET-FINGER is an international randomised, controlled, parallel-group, phase-IIb proof-of-concept clinical trial, where metformin is included through a trial-within-trial design. 600 participants will be recruited at three sites (UK, Finland, Sweden). Participants at increased risk of dementia based on vascular risk factors and cognitive screening, will be first randomised to the FINGER 2.0 intervention (lifestyle + metformin if eligible; active arm) or to receive regular health advice (control arm). Participants allocated to the FINGER 2.0 intervention group at risk indicators of T2D will be additionally randomised to receive metformin (2000 mg/day or 1000 mg/day) or placebo. The study duration is 2 years. The changes in global cognition (primary outcome, using a Neuropsychological Test Battery), memory, executive function, and processing speed cognitive domains; functional status; lifestyle, vascular, metabolic, and other dementia-related risk factors (secondary outcomes), will be compared between the FINGER 2.0 intervention and the control arm. The feasibility, potential interaction (between-groups differences in healthy lifestyle changes), and disease-modifying effects of the lifestyle-metformin combination will be exploratory outcomes. The lifestyle intervention is adapted from the original FINGER trial (diet, physical activity, cognitive training, monitoring of cardiovascular/metabolic risk factors, social interaction) to be consistently delivered in three countries. Metformin is administered as Glucophage®XR/SR 500, (500 mg oral tablets). The metformin/placebo treatment will be double blinded. Conclusion: MET-FINGER is the first trial combining a multimodal lifestyle intervention with a putative repurposed disease-modifying drug for cognitive impairment prevention. Although preliminary, its findings will provide crucial information for innovative precision prevention strategies and form the basis for a larger phase-III trial design and future research in this field. Trial registration: ClinicalTrials.gov (NCT05109169).

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  • 13.
    Compierchio, Angelo
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Humans and Technology.
    Illankoon, Prasanna
    University of Moratuwa, Moratuwa, Sri Lanka.
    A Neuroergonomics Mirror-Based Platform to Mitigate Cognitive Impairments in Fighter Pilots2024In: International Congress and Workshop on Industrial AI and eMaintenance 2023 / [ed] Uday Kumar; Ramin Karim; Diego Galar; Ravdeep Kour, Springer Nature, 2024, p. 31-43Conference paper (Refereed)
  • 14.
    Olsson, Erik
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Solid Mechanics. Department of Solid Mechanics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden.
    Jelagin, Denis
    Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden.
    Larsson, Stefan
    Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden.
    Chen, Feng
    Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden; Department of Highway and Railway Engineering, School of Transportation, Southeast University, Nanjing, People’s Republic of China.
    A numerical framework for modelling settlements of railway ballast layers2024In: Transportation Geotechnics, ISSN 2214-3912, Vol. 44, article id 101140Article in journal (Refereed)
    Abstract [en]

    Permanent deformation in ballast layers is a major contributing factor to the railway track geometry deterioration. In spite of a considerable amount of research on understanding and predicting performance of ballast layers, accurately capturing their settlements remains a challenge. In order to contribute to solving this important issue, a new numerical method for predicting ballast settlements is presented in this paper. This method is based on the finite element (FE) method combined with a constitutive model that captures permanent deformation accumulation in unbound materials under cyclic loading. This allows predicting permanent deformations of large structures and at large number of load cycles in a computationally efficient manner.

    The developed constitutive model is validated based on triaxial test measurements over wide range of loading conditions. Stress state in ballast layers has been examined with a 3D FE model, for several embankment structures and traffic load magnitudes. The determined stress distributions and loading frequencies were used as an input of the constitutive model to evaluate permanent strains and settlements of ballast layer. The influence of embankment structural designs and traffic loading magnitudes on the ballast layers settlements is examined and the results obtained are compared with the existing empirical performance models.

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  • 15.
    Sandin, Olle
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Solid Mechanics.
    Rodriguez, Juan Manuel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Solid Mechanics. School of Applied Sciences and Engineering, EAFIT University, Carrera 49 No. 7 South-50, Medellín, Colombia.
    Larour, Patrick
    voestalpine Stahl GmbH, voestalpine-Straße 3, 4020, Linz, Austria.
    Parareda, Sergi
    Unit of Metallic and Ceramic Materials, Eurecat, Centre Tecnològic de Catalunya, Plaça de la Ciència, 2, 08243, Manresa, Spain.
    Frómeta, David
    Unit of Metallic and Ceramic Materials, Eurecat, Centre Tecnològic de Catalunya, Plaça de la Ciència, 2, 08243, Manresa, Spain.
    Hammarberg, Samuel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Solid Mechanics.
    Kajberg, Jörgen
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Solid Mechanics.
    Casellas, Daniel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Solid Mechanics. Unit of Metallic and Ceramic Materials, Eurecat, Centre Tecnològic de Catalunya, Plaça de la Ciència, 2, 08243 Manresa, Spain.
    A particle finite element method approach to model shear cutting of high-strength steel sheets2024In: Computational Particle Mechanics, ISSN 2196-4378Article in journal (Refereed)
  • 16.
    Panahi, Parisa
    et al.
    Department of Chemical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran.
    Khorasani, Saied Nouri
    Department of Chemical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran.
    Mensah, Rhoda Afriyie
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.
    Das, Oisik
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.
    Neisiany, Rasoul Esmaeely
    Department of Polymer Engineering, Hakim Sabzevari University, Sabzevar 9617976487, Iran; Biotechnology Centre, Silesian University of Technology, Krzywoustego 8, 44-100 Gliwice, Poland.
    A review of the characterization methods for self-healing assessment in polymeric coatings2024In: Progress in organic coatings, ISSN 0300-9440, E-ISSN 1873-331X, Vol. 186, article id 108055Article, review/survey (Refereed)
  • 17.
    Swain, Sabyasachi
    et al.
    Deltaic Regional Centre, National Institute of Hydrology, Kakinada, India.
    Mishra, Prabhash Kumar
    Climate Hydrology Division, National Institute of Hydrology, Roorkee, India.
    Nandi, Saswata
    Sierra Nevada Research Institute, University of California Merced, Merced, USA.
    Pradhan, Biswajeet
    Centre for Advanced Modelling and Geospatial Information Systems, School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, Australia; Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Malaysia.
    Sahoo, Sashikanta
    Punjab Remote Sensing Centre, Ludhiana, 141004, India.
    Al-Ansari, Nadhir
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    A simplistic approach for monitoring meteorological drought over arid regions: a case study of Rajasthan, India2024In: Applied water science, ISSN 2190-5487, E-ISSN 2190-5495, Vol. 14, no 2, article id 36Article in journal (Refereed)
    Abstract [en]

    The commonly used precipitation-based drought indices typically rely on probability distribution functions that can be suitable when the data exhibit minimal discrepancies. However, in arid and semi-arid regions, the precipitation data often display significant discrepancies due to highly irregular rainfall patterns. Consequently, imposing any probability distributions on the data for drought analysis in such regions may not be effective. To address this issue, this study employs a novel drought index called the Discrepancy Precipitation Index (DPI), specifically designed for arid regions. Unlike traditional methods, the DPI does not impose a probability distribution on the precipitation data; instead, it relies on the discrepancy between the data and the mean value. Drought severity classifications (i.e., Drought-I, Drought-II, and Drought-III) are proposed based on the DPI values. The DPI is used to characterize and assess the meteorological drought years based on annual and monsoonal precipitation over nineteen districts in Western Rajasthan, India, during 1901–2019. Additionally, a novel statistic called Discrepancy Measure (DM) is employed to assess the degree of discrepancy in the precipitation climatology of the districts for annual and monsoon precipitation time series. Based on annual precipitation, Jaisalmer district exhibited the highest number of historical drought years (35), whereas three districts, i.e., Jhunjhunu, Dausa, and Bhilwara exhibited the lowest number of drought years (11). Similarly, based on monsoon precipitation, Jaisalmer and Bhilwara encountered the highest (34) and the lowest (11) number of drought years, respectively. The return period of Drought-II is lower for monsoon precipitation-based DPI as compared to that of the annual precipitation-based DPI for all the districts. The DM and DPI-based total number of droughts are found to be strongly correlated for both annual and monsoon precipitation. The DM value is highest for Jaisalmer and lowest for Bhilwara district. The findings reveal DPI as an efficient tool for assessing drought years, particularly in arid climatic conditions. Moreover, as the DM value increases for a precipitation series, the DPI becomes more effective in capturing drought events.

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  • 18.
    Wang, Liang
    et al.
    Department of Earth Sciences, ETH Zürich, Zürich, 8092, Switzerland.
    Zhang, Xue
    Department of Civil Engineering and Industrial Design, University of Liverpool, Liverpool, L69 3BX, UK.
    Meng, Jingjing
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Lei, Qinghua
    Department of Earth Sciences, ETH Zürich, Zürich, 8092, Switzerland; Department of Earth Sciences, Uppsala University, Uppsala, 75105, Sweden.
    A stable implicit nodal integration-based particle finite element method (N-PFEM) for modelling saturated soil dynamics2024In: Journal of Rock Mechanics and Geotechnical Engineering, ISSN 1674-7755Article in journal (Refereed)
  • 19.
    Wang, Di
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    Zhao, Jun
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    Claesson, Per
    Division of Surface and Corrosion Science, Department of Chemistry, KTH Royal Institute of Technology, Stockholm, SE-100 44, Sweden.
    Christakopoulos, Paul
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Rova, Ulrika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Matsakas, Leonidas
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Ytreberg, Erik
    Department of Mechanics and Maritime Sciences, Chalmers University of Technology, SE 412 96, Gothenburg, Sweden.
    Granhag, Lena
    Department of Mechanics and Maritime Sciences, Chalmers University of Technology, SE 412 96, Gothenburg, Sweden.
    Zhang, Fan
    Department of Engineering and Design, School of Engineering and Information, University of Sussex, Brighton, BN1 9RH, United Kingdom.
    Pan, Jinshan
    Division of Surface and Corrosion Science, Department of Chemistry, KTH Royal Institute of Technology, Stockholm, SE-100 44, Sweden.
    Shi, Yijun
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    A strong enhancement of corrosion and wear resistance of polyurethane-based coating by chemically grafting of organosolv lignin2024In: Materials Today Chemistry, E-ISSN 2468-5194, Vol. 35, article id 101833Article in journal (Refereed)
    Abstract [en]

    Corrosion and wear pose significant challenges to equipment operating in harsh environments. Thus, protective coatings are needed. Anti-corrosion and anti-wear coatings are traditionally fossil-based and often contain environmentally harmful additives. Achieving anti-corrosion and anti-wear coatings based on environmentally benign and sustainable materials is important and a significant challenge. This work focused on the development of organosolv lignin-based polyurethane (OS_lignin-PU) coatings. The coatings were synthesised and evaluated for corrosion protection using electrochemical impedance spectroscopy (EIS) and for wear properties using nanoindentation and nano scratch measurements. EIS revealed that the optimal lignin content for corrosion protection purposes in the OS_lignin-PU coatings was 15 wt%. Moreover, addition of 15 wt% lignin to the OS_lignin-PU coatings also enhanced their wear resistance, as evidenced by reduced thickness loss during tribometer tests. The nano scratch measurements revealed that OS_lignin-PU coatings containing 15 wt% lignin exhibited the lowest scratch depth and friction coefficient. It is found that the developed lignin-containing coating exhibits remarkable corrosion and wear resistance, making it a promising sustainable material in various applications for pursuing sustainable development.

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  • 20.
    Andrade, Elaine Cristina
    et al.
    Department of Mining and Petroleum Engineering, Polytechnic School, University of São Paulo, Av. Professor Mello Moraes, 2373, CEP 05508-900, São Paulo, SP, Brazil.
    Chelgani, Saeed Chehreh
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.
    de Salles Leal Filho, Laurindo
    Department of Mining and Petroleum Engineering, Polytechnic School, University of São Paulo, Av. Professor Mello Moraes, 2373, CEP 05508-900, São Paulo, SP, Brazil.
    A systematic study on gelatinization efficiency of starch by NaOH for enhanced hematite depression2024In: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 209, article id 108621Article in journal (Refereed)
    Abstract [en]

    Starch is a traditional depressant for hematite beneficiation by cationic reverse flotation separation from silicates. Alkali or thermal gelatinization must be used to prepare starch and promote its dissolution in water. In industry, gelatinization is typically carried out using sodium hydroxide at room temperature at different starch/NaOH mass ratios (SNMR). Surprisingly, no investigation has systematically studied the optimum SNMR for boosting hematite depression. This work examined the influence of starch gelatinization under various SNMR (3:1, 5:1, 7:1, and 9:1) on hematite depression (at pH = 10.5, 22 °C) by exploring flotation response (R), contact angle (θ), induction time (τ), hydrodynamic diameter (dH) of starch macromolecules, total energy of interaction starch/hematite (GTOT), based on its two components: the attractive Lifshitz-van der Waals energy (GLW) and attractive/repulsive electrostatic energy (GEL). Flotation test results indicated that SNMR = 5:1 promoted the lowest hematite recovery (14.8 %), coupled with the highest induction time (τ = 55 ms) and the lowest contact angle (θ = 11°). The hydrodynamic diameter (dH) of macromolecules in solutions prepared under different SNMR was determined by Dynamic Light Scattering, showing three peaks: amylopectin (350 < dH < 420 nm), amylose (50 < dH < 100 nm) and debris from gelatinization (dH ∼ 5000 nm). Since the latter only occurred in solutions prepared under SNMR of 7:1 and 9:1, deficient hematite depression might be caused by incomplete gelatinization. As amylopectin is the starch component that is responsible for its depressant ability, larger amylopectin macromolecules (dH = 411 nm) found in solutions prepared at SNMR = 5:1 contrast with smaller macromolecules (dH = 353 nm) produced at SNMR = 3:1. Considering starch macromolecules as a sphere, and hematite&apos;s surface as a plane; GLW, GEL, and GTOT were calculated in function of the sphere/plane separation distance (2 nm < H < 20 nm). GLW was determined based on the assessment of the Hamaker constant of the starch/water/hematite system (2.9 × 10−20J < A132 < 3.3 × 10−20J), whereas GEL was determined based on the zeta potential of starch (−2mV < ζ1 < −4mV) and hematite (ζ2 = −29 mV). GTOT for starch gelatinized at SNMR = 5:1 (−502.9 × 10−21 J) is greater than GTOT for starch prepared at SNMR = 3:1 (−468.8 × 10−21 J) and SNMR = 7:1 (−469.0 × 10−21 J), at a confidence level of 95 %. These results corroborate the more intensive hematite depression by starch prepared at SNMR = 5:1 compared to the other values explored by this study.

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  • 21.
    Kumari, Jaya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A System-of-Systems Approach for Enhancing Asset Management of Railways2024Doctoral thesis, comprehensive summary (Other academic)
  • 22.
    Higashitani, Yuko
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements. DENSO CORPORATION, 1–1 Showa-Cho, Kariya-shi, Aichi 448–8661, Japan.
    Kawabata, Sanemasa
    DENSO CORPORATION, 1–1 Showa-Cho, Kariya-shi, Aichi 448–8661, Japan.
    Björling, Marcus
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    Almqvist, Andreas
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    A traction coefficient formula for EHL point contacts operating in the linear isothermal region2024In: Tribology International, ISSN 0301-679X, E-ISSN 1879-2464, Vol. 193, article id 109452Article in journal (Refereed)
    Abstract [en]

    Many mechanical systems including rolling/sliding parts, require traction data across a spectrum of operating conditions to predict their motion effectively. Numerous studies have examined the thermal effects and shear-thinning concerning the traction curve, but only a few have focused on the traction coefficient in the linear isothermal regime for low SRR. In this work, we investigate traction coefficient characteristics of EHL point contacts in the linear isothermal regime, over a wide range of operational conditions. To this end, we conduct numerical simulations utilizing a fully-coupled finite element-based model, resulting in a prediction formula for the traction coefficient slope. With this formula, the traction coefficient slope could be predicted for the operating conditions considered.

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  • 23.
    Tadaros, Marduch
    et al.
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. Communications and Transport Systems, Department of Science and Technology, Linköping University, Norrköping, 60174, Sweden.
    Sifaleras, Angelo
    Department of Applied Informatics, School of Information Sciences, University of Macedonia, 156 Egnatia Str., Thessaloniki 54636, Greece.
    Migdalas, Athanasios
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.
    A variable neighborhood search approach for solving a real-world hierarchical multi-echelon vehicle routing problem involving HCT vehicles2024In: Computers & Operations Research, ISSN 0305-0548, E-ISSN 1873-765X, Vol. 165, article id 106594Article in journal (Refereed)
    Abstract [en]

    This paper studies the Hierarchical Multi-Switch Multi-Echelon VRP (HMSME-VRP), a newly introduced VRP variant based on a real-world case involving High Capacity Vehicles (HCV). The problem originates from the policies of a distribution company in the Nordic countries where HCVs of up to 34.5 m and up to 76 tons are allowed. The HMSME-VRP offer a new way to model distribution problems to cover large geographical areas without substantial costs in infrastructure. Furthermore, it adds complexity to the standard VRP and, as such, remains NP-hard and difficult to solve to optimality. Indeed, it has been demonstrated that only very small instances can be solved to optimality by a commercial solver. Thus, in order to handle instances of real-world size, we propose two General Variable Neighborhood Search (GVNS) procedures, the second of which is adaptive, utilizing an intelligent reordering mechanism. In order to evaluate the proposed procedures, 48 benchmark instances of various sizes and characteristics are generated and made publicly available, comprising of clustered, random, and semi-clustered customers. The computational results show that both GVNS procedures outperform the exact solver. Additionally, the adaptive version outperforms the conventional version based on both average and best solutions. Furthermore, we present a statistical analysis to verify the superiority of the adaptive version.

  • 24.
    Brandau, Benedikt
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development. JENOPTIK Optical Systems GmbH, System Development Advanced Manufacturing, Göschwitzerstraße 25, 07745 Jena, Germany.
    Brueckner, Frank
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development. Fraunhofer Institute for Material and Beam Technology IWS, Winterbergstraße 28, 01277 Dresden, Germany.
    Kaplan, Alexander F. H.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Absorbance determination of a powder bed by high resolution coaxial multispectral imaging in laser powder bed fusion2024In: Optics and Laser Technology, ISSN 0030-3992, E-ISSN 1879-2545, Vol. 168, article id 109780Article in journal (Refereed)
    Abstract [en]

    This study presents an approach for in-situ monitoring of laser powder bed fusion. Using standard laser optics, coaxial high-resolution multispectral images of powder beds are acquired in a pre-objective scanning configuration. A continuous overview image of the entire 114 × 114 mm powder bed can be generated, detecting objects down to 20 µm in diameter with a maximum offset of 22–49 µm. Multispectral information is obtained by capturing images at 6 different wavelengths from 405 nm to 850 nm. This allows in-line determination of the absorbance of the powder bed with a maximum deviation of 2.5% compared to the absorbance spectra of established methods. For the qualification of this method, ray tracing simulations on powder surfaces and tests with 20 different powders have been carried out. These included different particle sizes, aged and oxidized powders.

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  • 25.
    Iermolenko, Olga
    et al.
    Nord University Business School, Bodø, Norway.
    Hersinger, Anders
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.
    Accounting for a mining company’s transformation in Ukraine2024In: Meditari Accountancy Research, ISSN 2049-372X, Vol. 32, no 1, p. 123-150Article in journal (Refereed)
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  • 26.
    Wei, Haoyu
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Accumulation and Composition of Gully Pot Sediments under Varying Anthropogenic Activities2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Gully pots (GPs) are an integral urban drainage component, contributing to conveying runoff from urban surfaces and reducing the load of solids and associated contaminants entering downstream piped systems and receiving waters. Over time, the silting-up of GPs impairs their hydraulic performance, increasing the risk of GP blockage-induced flood events and reducing solids retention performance. These challenges are typically addressed through GP emptying programmes. However, current GP maintenance strategies lack clear aims and a robust evidence-base, against which their effectiveness can be benchmarked. The overall aim of this doctoral thesis is to enhance understanding of the factors influencing the physicochemical properties and accumulation of solids in GPs, thereby laying the groundwork for further assessment and optimisation of GP maintenance strategies. The study encompasses various anthropogenic factors such as land use types, seasonal activities, traffic conditions, environmental regulatory measures, GP design and catchment characteristics. Research reported in this thesis includes both desk-based modelling (e.g. a study on sediment scour behaviours), and the results of an extensive field sampling campaign (sediments from a total of 87 GPs were assessed for dry masses, particle size distribution (PSD) and a range of conventional and emerging urban and traffic-related substances).

    The considerable variations in physicochemical properties, mass accumulation rates of sediments and associated contaminants in GPs question the utility of the prevalent generalised maintenance strategy. Although GPs in trafficked roads showed significantly higher solids mass accumulation rates compared to those in non-trafficked catchments, this factor alone could not fully explain observed variations. For example, whilst selected typically traffic-sourced contaminants such as 4-tert-octylphenol (OP) and heavy-molecular-weight polycyclic aromatic hydrocarbons (PAH-H) exhibited significantly higher concentrations in GP sediments from trafficked roads, further typically-traffic-related pollutants (e.g. aliphatic hydrocarbon > C16-C35 and Zn), as well as 4-nonylphenol (NP) and monobutyltin (MBT) were reported for GPs located in commercial and car parking land-use types. In terms of temporal dynamics, winter-spring road safety measures did not consistently result in significantly higher solids mass accumulation rates compared to summer-autumn accumulation data. However, where present, a greater influence of winter-spring road safety measures was identified under certain conditions. For example, GPs along straight roads with adjacent pedestrian/bicycle paths showed an up-to 130-fold increase in solids accumulation rates following winter-spring accumulation, largely due to the practice of using coarse traction grits in this road feature type. Synergistic impacts of winter-spring road safety measures and road layout features were also observed. This includes amplified tyre and road wear (a function of the combined use of studded tyres, traction grits and frequent braking at roundabouts) is identified as contributing to e.g. significantly higher mass fraction of <63 µm sediments and concentrations of Zn, Cd, OP, selected PAHs and phthalates in corresponding GPs following winter-spring accumulation. Additionally, significant temporal changes in basic parameters of GP sediments such as pH, electrical conductivity (EC) and total organic carbon (TOC) were identified, indicating substance phase changes (e.g. adsorption/desorption) at solid-liquid interfaces should be anticipated, and their impact considered when assessing GP sediment management needs.

    This research also contributes to sediment management through the characterisation of GP sediments for a broad list of contaminants. The comparison of sediment substance concentrations with Predicted No-Effect Concentrations (PNECs) (and, where these are not available, with Norwegian guideline values) indicated that 31 substances in at least one investigated GP exceeded threshold values. This demonstrates that GPs can accumulate contaminated sediments and underscores the need to revisit the role of GPs in mitigating runoff quality (and quantity) as part of an integrated urban stormwater management plan.

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  • 27.
    Yin, Xuan
    et al.
    College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, 100029, China.
    Pang, Haosheng
    Chinese Aeronautical Establishment, Beijing, 100012, China.
    Liu, Huan
    State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
    Zhao, Jun
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements. School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China.
    Zhang, Bing
    College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, 100029, China.
    Liu, Dameng
    State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
    Shi, Yijun
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    Achieving ultralow friction under high pressure through operando formation of PbS QDs/graphene heterojunction with 0D/1D nanostructure2024In: Carbon, ISSN 0008-6223, E-ISSN 1873-3891, Vol. 218, article id 118748Article in journal (Refereed)
    Abstract [en]

    In this work, ultralow friction (0.054) of graphene was achieved under high contact pressure (1.03 GPa) and atmosphere environment via the operando formation of PbS quantum dots (QDs)/graphene heterojunction at the frictional interface. It is found that PbS QDs are trapped in graphene nanosheets via shear-induced rearrangement for obtaining the PbS QDs/graphene heterojunctions, which provide an excellent rolling effect to lower friction. It is also found that the heterogeneous PbS QDs/graphene tribofilms have a strong Pb-enriched function and heterojunction nanorod phase. Our objective is to uncover the physical and chemical mechanisms governing the friction of 0D/1D nanostructures within PbS QDs/graphene heterostructures through our studies. This research will enhance our comprehension of nanomaterials&apos; frictional behavior while offering valuable guidance and optimization strategies for their application in mechanical engineering and functional nanomaterials. Consequently, our efforts aim to foster the advancement of nanoscience and technology, leading to additional scientific and technological breakthroughs.

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  • 28.
    Foorginezhad, S.
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Zerafat, M. M.
    Faculty of Advanced Technologies, Nano-Chemical Engineering Department, Shiraz University, Shiraz, 71348-51154, Iran.
    Asadnia, M.
    School of Engineering, Macquarie University, Sydney, New South Wales, 2109, Australia.
    Rezvannasab, Gh
    Faculty of Advanced Technologies, Nano-Chemical Engineering Department, Shiraz University, Shiraz, 71348-51154, Iran.
    Activated porous carbon derived from sawdust for CO2 capture2024In: Materials Chemistry and Physics, ISSN 0254-0584, E-ISSN 1879-3312, Vol. 317, article id 129177Article in journal (Refereed)
    Abstract [en]

    Mitigation of greenhouse gas emissions, especially CO2, highlights the critical demand for efficient CO2 capture technologies. This is due to their essential role in climate change and their profound impact on global ecosystems and human well-being. Activated carbons have emerged as promising candidates for CO2 capture due to their availability, cost-effectiveness, and tunable properties. In this study, activated carbons were synthesized from sawdust carbonized at various temperatures within the 700–1100 °C range and subsequently activated using CO2. Comprehensive characterization was conducted through SEM, FESEM, XRD, TGA, and FTIR techniques to assess the properties. The results reveal that carbonization at 1000 °C yielded an activated carbon with a hierarchical and microporous structure, featuring surface area, pore volume, and pore size of 1651.34 m2/g, 0.69 cm³/g, and <1.76 nm, respectively. Remarkably, this activated carbon exhibited promising CO2 uptake of 9.2 mmol/g at 25 °C and 1 bar. Moreover, a remarkable recyclability over 10 cycles demonstrates its potential for practical CO2 capture applications. Furthermore, the synthesized activated carbon exhibited high selectivity for CO2 over N2 (85/15 v/v), reaching 40.2 at 1 bar and 25 °C. These findings underscore the viability of the as-prepared activated carbon as a desired candidate for efficient and selective CO2 capture, contributing to the ongoing efforts to mitigate the impact of anthropogenic CO2 emissions to the environment.

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  • 29.
    Forsberg, Hanna
    Luleå University of Technology, Department of Health, Learning and Technology, Health, Medicine and Rehabilitation.
    Active school transportation: Understanding the parental decision-making process2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Few children and adolescents reach the recommended levels of daily physical activity. This trend is evident in the countries examined in this thesis: Sweden and Spain. In efforts to reverse the current trend, active school transportation (AST) and independent mobility (IM) have been suggested as opportunities to increase levels of physical activity. Unfortunately, AST and IM have decreased during recent decades; consequently, initiatives promoting such behaviors have been called for. Parents are the main decision-makers on a child’s use of AST and IM, and thus, understanding their decisions is important in efforts to promote such behaviors. The overarching aim of this thesis was to increase the understanding of the parental decision-making process concerning their children’s active transport to school.

    This thesis applied an exploratory sequential design, with both interview (qualitative) and cross-sectional (quantitative) designs used to attain the overall aim. Data was collected through interviews with 20 parents (I) and two surveys: the PILCAST (Parents intentions to let their child use AST) questionnaire (II-III) and the PACO (Pedalea y Anda COlegio [Cycle and walk to school]) family questionnaire (IV). In total, 1024 responses from parents were collected with the PILCAST questionnaire (II). In paper III, a sub-sample of 610 was extracted from the 1024, based on parents responding “yes” or “no” to participation in an AST intervention. In paper IV, a total of 573 parents were included in the study. Data was analyzed with content analysis (I), descriptive statistics (II-IV), confirmatory factor analysis (II), linear regression analysis (II-IV), and logistic regression analysis (IV).

    The main findings showed that parents’ decisions regarding AST and IM were influenced by social norms, which was reflected in appearing to be a good parent and by what significant others do in their vicinity and neighborhood (I, II, IV). The importance of social norms applied to both Swedish and Spanish parents when it comes to AST. Some, gender differences were found, showing that they might play a more important role for parents of girls when it comes to AST and IM. Further, the findings showed that attitudes influence decisions, which was reflected in how parents master everyday life by sometimes choosing what is most convenient, even though they are aware of the benefits of AST (I-II). Parents identified factors both impeding and facilitating the use of AST, while safety and trusting the child were found to be important (I-II). The findings also indicate that the intervention within the Sustainable Innovation for Children Transporting Actively (SICTA) project might positively influence parents’ beliefs about AST (III). In addition, there seems to be a habitual factor involved in the parental decision-making process (II). Differences were found between parents’ decisions to let their child cycle to school compared to letting their child walk to school (II). Finally, the parental decision-making process seems to be influenced by the child’s age and the distance between home and school (I, II, IV). The PILCAST questionnaire showed acceptable validity and reliability.

    In conclusion, the findings show that when aiming to promote AST and IM, social acceptance is important. This concerns both other people’s judgments of parenting and what other important referent groups are doing, encompassing the visibility of AST and IM in the parents’ vicinity and neighborhoods. Attention given to gender differences could be beneficial as well. Further, it is also important to understand the prerequisites of modern family life. It is likely that strengthening positive attitudes in parents could promote AST, but the practice also needs to be in line with their everyday life tasks. Efforts should also be made to strengthen the factors that facilitate AST. From a parental perspective, this includes safety and being supported in gaining trust in their children and their children’s capabilities with respect to the age of the children. Habit seems to play an important role, and to encourage parents to form new habits, it might be beneficial to launch AST interventions along with contextual changes, as these might open a window for change, which could occur in the transition between preschool and primary school. It could be beneficial to consider cycling and walking as different behaviors because walking seems to be more dependent on the distance to school than cycling. Further, the PILCAST questionnaire was valid and reliable, providing an increased understanding of these behaviors from a parental perspective. Finally, to make children’s use of active transport to school the more favorable choice, it seems worthwhile not only to give children the opportunity to participate but also to involve parents and address their beliefs when designing interventions.

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  • 30.
    Saback, Vanessa
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.
    Gonzalez-Libreros, Jaime
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.
    Daescu, Cosmin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering. Department of Civil Engineering and Installations (CCI), Politehnica University of Timisoara, Timisoara, Romania.
    Popescu, Cosmin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering. SINTEF Narvik AS, Narvik, Norway.
    Garmabaki, Amir Soleimani
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Sas, Gabriel
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.
    Adapting to climate change: snow load assessment of snow galleries on the Iron Ore Line in Northern Sweden2024In: Frontiers in Built Environment, E-ISSN 2297-3362, Vol. 9Article in journal (Refereed)
    Abstract [en]

    The snow galleries along the Iron Ore railway line in northern Sweden have facedproblems in recent years due to increasingly large snow loads, and several gallerieshave been damaged. These incidents motivated an evaluation of the maximumload supported by the galleries before collapse, which is presented in this study. In2021, a monitoring system was installed in one of the main frames of two snowgalleries built in the 1950s to follow up with temperature and displacements,including a trigger that sends out a warning message when a critical load isreached. A literature review on snow loads was performed, followed bycalculations on snow distribution on the galleries based on the Eurocodes andNational Swedish Standards. Finite element 2D and 3D models were created usingAxisVM to accurately assess the efforts in the structural elements. Analysis anddiscussion are complemented by observations from site visits. It was concludedthat the critical loads supported by the galleries are lower than the requirements oftoday’s standards, but since secondary construction elements were damagedbefore the main frames reached their full capacity, no major collapse has yet takenplace. The cobweb effect (load re-distribution between the neighboring elementsin a 3D structure) influenced the behavior of the galleries in the 3D analysis and thecapacity of the main frames proved to be significantly increased compared to the2D assessment.

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  • 31.
    Papadopoulos, Nikolaos G.
    et al.
    Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK; Allergy Department, 2nd Paediatric Clinic, National and Kapodistrian University of Athens, Athens, Greece.
    Akdis, Cezmi
    Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland, Christine Kühne-Center for Allergy Research and Education (CK-CARE), Davos, Switzerland.
    Akdis, Mubeccel
    Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland, Christine Kühne-Center for Allergy Research and Education (CK-CARE), Davos, Switzerland.
    Damialis, Athanasios
    Department of Ecology, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece.
    Esposito, Giuseppina
    Bio Check Up (BCU), Naples, Italy.
    Fergadiotou, Ioana
    INLECOM INNOVATION, Kifissia, Greece.
    Goroncy, Christian
    DIN Deutsches Institut fuer Normung EV, Berlin, Germany.
    Guitton, Pierre
    TEQOYA Company, Paris, France.
    Gotua, Maia
    Center for Allergy and Immunology Research (CAIR), Tbilisi, Georgia.
    Erotokritou, Kleanthis
    CY.R.I.C Cyprus Research and Innovation Center Ltd, Nicosia, Cyprus.
    Jartti, Tuomas
    PEDEGO Research Unit, University of Oulu, Oulu, Finland; Department of Pediatrics, Oulu University Hospital, Oulu, Finland; Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland.
    Murray, Clare
    Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK.
    Nenes, Athanasios
    Laboratory of Atmospheric Processes and their Impacts, School of Architecture, Civil and Environmental Engineering, Swiss Institute of Technology, Lausanne, Switzerland.
    Nikoletseas, Sotirios
    Computer Engineering and Informatics Department, University of Patras, Patras, Greece.
    Finotto, Susetta
    Molecular Pneumology Department, University Hospital of Erlangen, Erlangen, Germany.
    Pandis, Spyros N.
    Institute of Chemical Engineering Sciences (ICEHT), Foundation for Research and Technology Hellas (FORTH), Patras, Greece.
    Ramiconi, Valeria
    The European Federation of Allergy and Airways Diseases Patients‘ Association (EFA), Brussels, Belgium.
    Simpson, Angela
    Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK.
    Soudunsaari, Aki
    NAAVA, Helsinki, Finland.
    Stårbröst, Anna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Staiano, Maria
    Institute of Food Science, CNR Italy, Avellino, Italy.
    Varriale, Antonio
    Institute of Food Science, CNR Italy, Avellino, Italy; URT-ISA, CNR at Department of Biology, University of Naples Federico II, Naples, Italy.
    Xepapadaki, Paraskevi
    Allergy Department, 2nd Paediatric Clinic, National and Kapodistrian University of Athens, Athens, Greece.
    Zuberbier, Torsten
    Institute of Allergology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Allergology and Immunology, Berlin, Germany; Global Allergy & Asthma European Network of Excellence-GA, 2, LEN, Berlin, Germany.
    Annesi-Maesano, Isabella
    Department of Allergic and Respiratory Disease, Institut Desbrest of Epidemiology and Public Health, University of Montpellier and INSERM, Montpellier University Hospital, Montpellier, France.
    The SynAir-G Consortium,
    Addressing adverse synergies between chemical and biological pollutants at schools—The ‘SynAir-G’ hypothesis2024In: Allergy. European Journal of Allergy and Clinical Immunology, ISSN 0105-4538, E-ISSN 1398-9995, Vol. 79, no 2, p. 294-301Article in journal (Refereed)
    Abstract [en]

    While the number and types of indoor air pollutants is rising, much is suspected but little is known about the impact of their potentially synergistic interactions, upon human health. Gases, particulate matter, organic compounds but also allergens and viruses, fall within the ‘pollutant’ definition. Distinct populations, such as children and allergy and asthma sufferers are highly susceptible, while a low socioeconomic background is a further susceptibility factor; however, no specific guidance is available. We spend most of our time indoors; for children, the school environment is of paramount importance and potentially amenable to intervention. The interactions between some pollutant classes have been studied. However, a lot is missing with respect to understanding interactions between specific pollutants of different classes in terms of concentrations, timing and sequence, to improve targeting and upgrade standards. SynAir-G is a European Commission-funded project aiming to reveal and quantify synergistic interactions between different pollutants affecting health, from mechanisms to real life, focusing on the school setting. It will develop a comprehensive and responsive multipollutant monitoring system, advance environmentally friendly interventions, and disseminate the generated knowledge to relevant stakeholders in accessible and actionable formats. The aim of this article it to put forward the SynAir-G hypothesis, and describe its background and objectives.

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  • 32.
    Hultman, Lars
    et al.
    Thin Film Physics Division, Department of Physics, IFM, Linköping University, Linköping, Sweden.
    Mazur, Sara
    Knut and Alice Wallenberg Foundation, Stockholm, Sweden.
    Ankarcrona, Caroline
    Knut and Alice Wallenberg Foundation, Stockholm, Sweden.
    Palmqvist, Anders
    Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Abrahamsson, Maria
    Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Antti, Marta-Lena
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science.
    Baltzar, Malin
    H2 Green Steel, Stockholm, Sweden.
    Bergström, Lennart
    Department of Materials and Environmental Chemistry, Stockholm University, Stockholm, Sweden.
    de Laval, Pontus
    Knut and Alice Wallenberg Foundation, Stockholm, Sweden.
    Edman, Ludvig
    The Organic Photonics and Electronics Group, Department of Physics, Umeå University, Umeå, Sweden.
    Erhart, Paul
    Department of Physics, Chalmers University of Technology, Gothenburg, Sweden.
    Kloo, Lars
    Applied Physical Chemistry, Department of Chemistry, KTH Royal Institute of Technology, Stockholm, Sweden.
    Lundberg, Mats W.
    Sandvik AB, Stockholm, Sweden.
    Mikkelsen, Anders
    NanoLund Center for Nanoscience, Lund University, Lund, Sweden; Department of Physics, Lund University, Lund, Sweden.
    Moons, Ellen
    Materials Science Research, Department of Engineering and Physics, Karlstad University, Karlstad, Sweden.
    Persson, Cecilia
    Department of Materials Science and Engineering, Uppsala University, Uppsala, Sweden.
    Rensmo, Håkan
    Condensed Matter Physics of Energy Materials, Division of X-ray Photon Science, Department of Physics and Astronomy, Uppsala University, Uppsala, Sweden.
    Rosén, Johanna
    Materials Design Division, Department of Physics, Chemistry and Biology (IFM), Linköping University, Linköping, Sweden.
    Rudén, Christina
    Department of Environmental Science, Stockholm University, Stockholm, Sweden.
    Selleby, Malin
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Sundgren, Jan-Eric
    Swedish Association of Engineering Industries, Stockholm, Sweden.
    Dick Thelander, Kimberly
    Centre for Analysis and Synthesis and NanoLund, Lund University, Lund, Sweden.
    Tybrandt, Klas
    Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, Norrköping, Sweden.
    Weihed, Pär
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering.
    Zou, Xiaodong
    Department of Materials and Environmental Chemistry, Stockholm University, Stockholm, Sweden.
    Åstrand, Maria
    Northvolt AB, Stockholm, Sweden.
    Björkman, Charlotte Platzer
    Department of Physics and Astronomy, Uppsala University, Uppsala, Sweden.
    Schneider, Jochen M.
    Materials Chemistry, RWTH Aachen University, Aachen, Germany.
    Eriksson, Olle
    Department of Physics and Astronomy, Uppsala University, Uppsala, Sweden.
    Berggren, Magnus
    Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, Norrköping, Sweden.
    Advanced materials provide solutions towards a sustainable world2024In: Nature Materials, ISSN 1476-1122, E-ISSN 1476-4660, Vol. 23, no 2, p. 160-161Article in journal (Other academic)
  • 33.
    Ilyas, Farva
    et al.
    Department of Materials Science and Engineering, College of Transportation Engineering, Dalian Maritime University, Dalian, 116026, PR China; Shanghai Jiao Tong University, Shanghai 200240, China.
    Fazal, Hira
    Shanghai Jiao Tong University, Shanghai 200240, China.
    Ahmed, Muhktiar
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Iqbal, Asma
    Shanghai Jiao Tong University, Shanghai 200240, China.
    Ishaq, Muhammad
    Shanghai Jiao Tong University, Shanghai 200240, China.
    Jabeen, Maher
    Shanghai Jiao Tong University, Shanghai 200240, China.
    Butt, Madiha
    Shanghai Jiao Tong University, Shanghai 200240, China.
    Farid, Sumbal
    Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
    Advances in ionic liquids as fluorescent sensors2024In: Chemosphere, ISSN 0045-6535, E-ISSN 1879-1298, Vol. 352, article id 141434Article, review/survey (Refereed)
  • 34.
    González Chávez, Clarissa A.
    et al.
    Department of Industrial and Material Sciences, Chalmers University of Technology, Gothenburg, Sweden.
    Brynolf, Selma
    Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden.
    Despeisse, Mélanie
    Department of Industrial and Material Sciences, Chalmers University of Technology, Gothenburg, Sweden.
    Johansson, Björn
    Department of Industrial and Material Sciences, Chalmers University of Technology, Gothenburg, Sweden.
    Rönnbäck, Anna Öhrwall
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Humans and Technology.
    Rösler, Jonathan
    Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland.
    Stahre, Johan
    Department of Industrial and Material Sciences, Chalmers University of Technology, Gothenburg, Sweden.
    Advancing sustainability through digital servitization: An exploratory study in the maritime shipping industry2024In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 436, article id 140401Article in journal (Refereed)
    Abstract [en]

    Global businesses are transforming towards capturing more value from services, a business model transition called servitization. Digital servitization can help create and maintain a competitive advantage, as well as offering opportunities to tackle major challenges related to environmental pressures and rapidly changing market conditions. This study aims to bridge the gap between the theory of digital servitization and its implementation in the maritime shipping sector. This paper presents a multi-case study that explores the status, perceived challenges, and enablers for the adoption of digital servitization. Empirical data were collected from interviews with 13 companies and analyzed using the PESTEL and DPSIR frameworks. The results are presented across three categories based on the PESTEL framework: organizational context, global priorities, and sustainability. This study contributes to theory by providing empirical insights from the status of digital servitization in the maritime shipping industry. Also, it identifies challenges and needs that can support the transition towards digital servitization and the development of more sustainable solutions. Future research avenues are suggested to advance digital servitization in other industrial sectors.

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  • 35.
    Vacalopoulou, A.
    et al.
    ILSP / Athena R.C., GREECE.
    Gardelli, Viktor
    Luleå University of Technology, Department of Health, Education and Technology, Education, Language, and Teaching.
    Karafyllidis, T.
    University of Cyprus, CYPRUS.
    Liwicki, Foteini
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Mokayed, Hamam
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Papaevripidou, M.
    University of Cyprus, CYPRUS.
    Paraskevopoulos, G.
    ILSP / Athena R.C., GREECE.
    Stamouli, S.
    ILSP / Athena R.C., GREECE.
    Katsamanis, A.
    ILSP / Athena R.C., GREECE.
    Katsouros, V.
    ILSP / Athena R.C., GREECE.
    AI4EDU: An Innovative Conversational Ai Assistant For Teaching And Learning2024In: INTED2024 Conference Proceedings / [ed] Luis Gómez Chova; Chelo González Martínez; Joanna Lees, IATED Academy , 2024, p. 7119-7127Conference paper (Refereed)
  • 36.
    Kumar, Pankaj
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science.
    Eriksson, Martin
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science.
    Kharytonau, Dzmitry S.
    Electrochemistry and Corrosion Laboratory, Jerzy Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences, 30-239 Krakow, Poland.
    You, Shujie
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science.
    Natile, Marta Maria
    National Research Council (CNR), Institute of Condensed Matter Chemistry and Technologies for Energy (ICMATE), via F. Marzolo 1, 35131 Padova, Italy; Department of Chemical Sciences, University of Padova, via F. Marzolo 1, 35131 Padova, Italy.
    Vomiero, Alberto
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science. Department of Molecular Sciences and Nanosystems, Ca’ Foscari University of Venice, via Torino 155, 30172 Venezia Mestre, Italy.
    All-Inorganic Hydrothermally Processed Semitransparent Sb2S3 Solar Cells with CuSCN as the Hole Transport Layer2024In: ACS Applied Energy Materials, E-ISSN 2574-0962, Vol. 7, no 4, p. 1421-1432Article in journal (Refereed)
    Abstract [en]

    Published by American Chemical Society.An inorganic wide-bandgap hole transport layer (HTL), copper(I) thiocyanate (CuSCN), is employed in inorganic planar hydrothermally deposited Sb2S3 solar cells. With excellent hole transport properties and uniform compact morphology, the solution-processed CuSCN layer suppresses the leakage current and improves charge selectivity in an n-i-p-type solar cell structure. The device without the HTL (FTO/CdS/Sb2S3/Au) delivers a modest power conversion efficiency (PCE) of 1.54%, which increases to 2.46% with the introduction of CuSCN (FTO/CdS/Sb2S3/CuSCN/Au). This PCE is a significant improvement compared with the previous reports of planar Sb2S3 solar cells employing CuSCN. CuSCN is therefore a promising alternative to expensive and inherently unstable organic HTLs. In addition, CuSCN makes an excellent optically transparent (with average transmittance >90% in the visible region) and shunt-blocking HTL layer in pinhole-prone ultrathin(<100 nm) semitransparent absorber layers grown by green and facile hydrothermal deposition. A semitransparent device is fabricated using an ultrathin Au layer (∼10 nm) with a PCE of 2.13% and an average visible transmittance of 13.7%.

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  • 37.
    Mariam, Iqra
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Bettiga, Maurizio
    Department of Life Sciences – LIFE, Division of Industrial Biotechnology, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden; Innovation Unit, Italbiotec Srl Società Benefit, Milan, Italy.
    Rova, Ulrika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Christakopoulos, Paul
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Matsakas, Leonidas
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Patel, Alok
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Ameliorating microalgal OMEGA production using omics platforms2024In: Trends in Plant Science, ISSN 1360-1385, E-ISSN 1878-4372Article, review/survey (Refereed)
    Abstract [en]

    Over the past decade, the focus on omega (ω)-3 fatty acids from microalgae has intensified due to their diverse health benefits. Bioprocess optimization has notably increased ω-3 fatty acid yields, yet understanding of the genetic architecture and metabolic pathways of high-yielding strains remains limited. Leveraging genomics, transcriptomics, proteomics, and metabolomics tools can provide vital system-level insights into native ω-3 fatty acid-producing microalgae, further boosting production. In this review, we explore ‘omics’ studies uncovering alternative pathways for ω-3 fatty acid synthesis and genome-wide regulation in response to cultivation parameters. We also emphasize potential targets to fine-tune in order to enhance yield. Despite progress, an integrated omics platform is essential to overcome current bottlenecks in optimizing the process for ω-3 fatty acid production from microalgae, advancing this crucial field.

  • 38.
    Prajapati, Deepak K.
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    Hansen, Jonny
    Electric Propulsion Development, Scania CV AB, Södertälje, Sweden.
    Björling, Marcus
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
    An assessment of the effect of surface topography on coefficient of friction for lubricated non-conformal contacts2024In: Frontiers in Mechanical Engineering, E-ISSN 2297-3079, Vol. 10, article id 1360023Article in journal (Refereed)
    Abstract [en]

    Determining an accurate state of lubrication is of utmost importance for the precise functionality of machine elements and to achieve elongated life and durability. In this work, a homogenized mixed-lubrication model is developed to study the effect of surface topographies on the coefficient of friction. Various measured real surface topographies are integrated in the model using the roughness homogenization method. The shear-thinning behavior of the lubricant is incorporated by employing the Eyring constitutive relation. Several Stribeck curves are generated to analyze the effect of roughness lays and root mean square (RMS) roughness on the coefficient of friction. The homogenized mixed lubrication model is validated against experimental rolling/sliding ball-on-disc results, and a good agreement between simulated and experimental coefficient of friction is found.

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  • 39.
    Seisa, Achilleas Santi
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Lindqvist, Bjorn
    Satpute, Sumeet Gajanan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Nikolakopoulos, George
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    An Edge Architecture for Enabling Autonomous Aerial Navigation with Embedded Collision Avoidance Through Remote Nonlinear Model Predictive Control2024In: Journal of Parallel and Distributed Computing, ISSN 0743-7315, E-ISSN 1096-0848, Vol. 188, article id 104849Article in journal (Other academic)
    Abstract [en]

    In this article, we present an edge-based architecture for enhancing the autonomous capabilities of resource-constrained aerial robots by enabling a remote nonlinear model predictive control scheme, which can be computationally heavy to run on the aerial robots' onboard processors. The nonlinear model predictive control is used to control the trajectory of an unmanned aerial vehicle while detecting, and preventing potential collisions. The proposed edge architecture enables trajectory recalculation for resource-constrained unmanned aerial vehicles in relatively real-time, which will allow them to have fully autonomous behaviors. The architecture is implemented with a remote Kubernetes cluster on the edge side, and it is evaluated on an unmanned aerial vehicle as our controllable robot, while the robotic operating system is used for managing the source codes, and overall communication. With the utilization of edge computing and the architecture presented in this work, we can overcome computational limitations, that resource-constrained robots have, and provide or improve features that are essential for autonomous missions. At the same time, we can minimize the relative travel time delays for time-critical missions over the edge, in comparison to the cloud. We investigate the validity of this hypothesis by evaluating the system's behavior through a series of experiments by utilizing either the unmanned aerial vehicle or the edge resources for the collision avoidance mission.

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  • 40.
    Mahmud, Tanjim
    et al.
    Department of Computer Science and Engineering, Rangamati Science and Technology University, Rangamati, 4500, Bangladesh.
    Barua, Koushick
    Department of Computer Science and Engineering, Rangamati Science and Technology University, Rangamati, 4500, Bangladesh.
    Habiba, Sultana Umme
    Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh.
    Sharmen, Nahed
    Department of Obstetrics and Gynecology, Chattogram Maa-O-Shishu Hospital Medical College, Chittagong, 4100, Bangladesh.
    Hossain, Mohammad Shahadat
    Department of Computer Science and Engineering, University of Chittagong, Chittagong 4331, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An Explainable AI Paradigm for Alzheimer’s Diagnosis Using Deep Transfer Learning2024In: Diagnostics, ISSN 2075-4418, Vol. 14, no 3, article id 345Article in journal (Refereed)
    Abstract [en]

    Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of individuals worldwide, causing severe cognitive decline and memory impairment. The early and accurate diagnosis of AD is crucial for effective intervention and disease management. In recent years, deep learning techniques have shown promising results in medical image analysis, including AD diagnosis from neuroimaging data. However, the lack of interpretability in deep learning models hinders their adoption in clinical settings, where explainability is essential for gaining trust and acceptance from healthcare professionals. In this study, we propose an explainable AI (XAI)-based approach for the diagnosis of Alzheimer’s disease, leveraging the power of deep transfer learning and ensemble modeling. The proposed framework aims to enhance the interpretability of deep learning models by incorporating XAI techniques, allowing clinicians to understand the decision-making process and providing valuable insights into disease diagnosis. By leveraging popular pre-trained convolutional neural networks (CNNs) such as VGG16, VGG19, DenseNet169, and DenseNet201, we conducted extensive experiments to evaluate their individual performances on a comprehensive dataset. The proposed ensembles, Ensemble-1 (VGG16 and VGG19) and Ensemble-2 (DenseNet169 and DenseNet201), demonstrated superior accuracy, precision, recall, and F1 scores compared to individual models, reaching up to 95%. In order to enhance interpretability and transparency in Alzheimer’s diagnosis, we introduced a novel model achieving an impressive accuracy of 96%. This model incorporates explainable AI techniques, including saliency maps and grad-CAM (gradient-weighted class activation mapping). The integration of these techniques not only contributes to the model’s exceptional accuracy but also provides clinicians and researchers with visual insights into the neural regions influencing the diagnosis. Our findings showcase the potential of combining deep transfer learning with explainable AI in the realm of Alzheimer’s disease diagnosis, paving the way for more interpretable and clinically relevant AI models in healthcare.

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  • 41.
    Rotari, Marta
    et al.
    Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark.
    Diaz, Valeria Fonseca
    Department of Biosystems, MeBioS division, KU Leuven, Leuven, Belgium.
    De Ketelaere, Bart
    Department of Biosystems, MeBioS division, KU Leuven, Leuven, Belgium.
    Kulahci, Murat
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark.
    An extension of PARAFAC to analyze multi-group three-way data2024In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 246, article id 105089Article in journal (Refereed)
    Abstract [en]

    This paper introduces a novel methodology for analyzing three-way array data with a multi-group structure. Three-way arrays are commonly observed in various domains, including image analysis, chemometrics, and real-world applications. In this paper, we use a practical case study of process modeling in additive manufacturing, where batches are structured according to multiple groups. Vast volumes of data for multiple variables and process stages are recorded by sensors installed on the production line for each batch. For these three-way arrays, the link between the final product and the observations creates a grouping structure in the observations. This grouping may hamper gaining insight into the process if only some of the groups dominate the controlled variability of the products. In this study, we develop an extension of the PARAFAC model that takes into account the grouping structure of three-way data sets. With this extension, it is possible to estimate a model that is representative of all the groups simultaneously by finding their common structure. The proposed model has been applied to three simulation data sets and a real manufacturing case study. The capability to find the common structure of the groups is compared to PARAFAC and the insights into the importance of variables delivered by the models are discussed.

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  • 42.
    Chen, Haizhou
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. College of Electromechanical Engineering, Qingdao University of Science and Technology, 266061 Qingdao, People’s Republic of China.
    Lin, Janet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Division of Product Realization, Mälardalen University, 63220 Eskilstuna, Sweden.
    Chen, Nian
    College of Economics and Management, Qingdao University of Science and Technology, 266061 Qingdao, People’s Republic of China.
    Xu, Guanji
    Qingdao Huihe Zhongcheng Intelligent Technology Ltd, 266108 Qingdao, People’s Republic of China.
    An integrated approach to evaluate the measurement capability and acceptability of acoustic emission sensors2024In: Measurement science and technology, ISSN 0957-0233, E-ISSN 1361-6501, Vol. 35, no 2, article id 025132Article in journal (Refereed)
  • 43.
    Hauashdh, Ali
    et al.
    Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, 86400, Malaysia.
    Nagapan, Sasitharan
    Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, 86400, Malaysia; Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
    Jailani, Junaidah
    Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, 86400, Malaysia.
    Gamil, Yaser
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering. Department of Civil Engineering, School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor, Malaysia .
    An integrated framework for sustainable and efficient building maintenance operations aligning with climate change, SDGs, and emerging technology2024In: Results in Engineering (RINENG), ISSN 2590-1230, Vol. 21, article id 101822Article in journal (Refereed)
    Abstract [en]

    While existing literature offers various frameworks, they primarily focus on traditional building maintenance procedures and overlook the importance of integrating sustainability, climate change, environmental factors, and emerging technologies. To address this gap, this research has developed a comprehensive framework that caters to current needs, challenges, and future priorities. The integrated framework for building maintenance operations aligns with the Sustainable Development Goals (SDGs), climate change mitigation and adaptation, the adoption of emerging technology, energy conservation, as well as safety, resilience, and effectiveness. The development of the framework encompassed four phases: pre-development phases 1 and 2, development phase 3, and validation phase 4. During this process, current issues and challenges were identified, impacts were assessed, and strategies were developed. The framework serves as a roadmap to address these challenges and requirements in future building maintenance operations, making significant contributions to all three dimensions of sustainability: environmental, social, and economic. In summary, this study offers a comprehensive and in-depth analysis of the current issues, challenges, and potential improvements and benefits in building maintenance operations, providing a practical guide for industry stakeholders and making a significant contribution to the existing body of knowledge.

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  • 44.
    Zhang, Liangwei
    et al.
    Department of Industrial Engineering, Dongguan University of Technology, Dongguan 523808, China.
    Lin, Jing
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Division of Product Realization, Mälardalen University, 63220, Eskilstuna, Sweden.
    Shao, Haidong
    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China.
    Yang, Zhe
    Department of Industrial Engineering, Dongguan University of Technology, Dongguan 523808, China.
    Liu, Biyu
    School of Economics and Management, Fuzhou University, Fuzhou 350116, China.
    Li, Chuan
    Department of Industrial Engineering, Dongguan University of Technology, Dongguan 523808, China.
    An unsupervised end-to-end approach to fault detection in delta 3D printers using deep support vector data description2024In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 72, p. 214-228Article in journal (Refereed)
    Abstract [en]

    Fault detection in 3D printers is crucial for safety and quality assurance, emphasizing proactive prediction over reactive rectification based on manufacturing factors. Presently, most detection techniques rely on shallow models with limited representational capabilities, necessitating manual feature extraction from the captured signals. This manual process is not only cumbersome and potentially costly but often requires intricate domain-specific knowledge. Additionally, these handcrafted features might not optimally distinguish between normal and faulty samples, potentially reducing prediction accuracy. In this study, we introduce an end-to-end approach using the Deep Support Vector Data Description model for fault detection in 3D printers. This design inherently facilitates automatic feature learning, where the features are synergistically optimized for fault detection. Our experiments leverage magnetic field signals for fault detection in 3D printers, using 1D convolutional layers to discern temporal signal patterns and wide kernels in the initial layer to mitigate high-frequency noise. Furthermore, our model can be easily adapted to integrate multi-channel signals for enhanced accuracy. Evaluations on real-world data from a delta 3D printer underscore the superiority of our method compared to existing alternatives.

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  • 45.
    Reetz, Susanne
    et al.
    Institute of Transportation Systems, German Aerospace Center (DLR), Braunschweig, 38108, Germany.
    Najeh, Taoufik
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lundberg, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Groos, Jörn
    Institute of Transportation Systems, German Aerospace Center (DLR), Braunschweig, 38108, Germany.
    Analysis of Local Track Discontinuities and Defects in Railway Switches Based on Track-Side Accelerations2024In: Sensors, E-ISSN 1424-8220, Vol. 24, no 2, article id 477Article in journal (Refereed)
    Abstract [en]

    Switches are an essential, safety-critical part of the railway infrastructure. Compared to open tracks, their complex geometry leads to increased dynamic loading on the track superstructure from passing trains, resulting in high maintenance costs. To increase efficiency, condition monitoring methods specific to railway switches are required. A common approach to track superstructure monitoring is to measure the acceleration caused by vehicle track interaction. Local interruptions in the wheel–rail contact, caused for example by local defects or track discontinuities, appear in the data as transient impact events. In this paper, such transient events are investigated in an experimental setup of a railway switch with track-side acceleration sensors, using frequency and waveform analysis. The aim is to understand if and how the origins of these impact events can be distinguished in the data of this experiment, and what the implications for condition monitoring of local track discontinuities and defects with wayside acceleration sensors are in practice. For the same experimental configuration, individual impact events are shown to be reproducible in waveform and frequency content. Nevertheless, with this track-side sensor setup, the different types of track discontinuities and defects (squats, joints, crossing) could not be clearly distinguished using characteristic frequencies or waveforms. Other factors, such as the location of impact event origin relative to the sensor, are shown to have a much stronger influence. The experimental data suggest that filtering the data to narrow frequency bands around certain natural track frequencies could be beneficial for impact event detection in practice, but differentiating between individual impact event origins requires broadband signals. A multi-sensor setup with time-synchronized acceleration sensors distributed over the switch is recommended.

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  • 46.
    Fornasiero, Alessandro
    et al.
    CeRiSM, Sport Mountain and Health Research Center, University of Verona, Rovereto, Italy; Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy.
    Fornoni, Simone
    Faculty of Sports and Exercise Sciences, University of Verona, Verona, Italy.
    Callovini, Alexa
    CeRiSM, Sport Mountain and Health Research Center, University of Verona, Rovereto, Italy; Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
    Todesco, Beatrice
    CeRiSM, Sport Mountain and Health Research Center, University of Verona, Rovereto, Italy; Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
    Savoldelli, Aldo
    CeRiSM, Sport Mountain and Health Research Center, University of Verona, Rovereto, Italy; Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.
    Schena, Federico
    CeRiSM, Sport Mountain and Health Research Center, University of Verona, Rovereto, Italy; Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
    Holmberg, Hans-Christer
    Luleå University of Technology, Department of Health, Education and Technology, Health, Medicine and Rehabilitation. Department of Physiology and Pharmacology, Biomedicum C5, Karolinska Institutet, Stockholm, Sweden.
    Pellegrini, Barbara
    CeRiSM, Sport Mountain and Health Research Center, University of Verona, Rovereto, Italy; Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy.
    Bortolan, Lorenzo
    CeRiSM, Sport Mountain and Health Research Center, University of Verona, Rovereto, Italy; Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
    Analysis of Sprint Ski Mountaineering Performance2024In: International Journal of Sports Physiology and Performance, ISSN 1555-0265, E-ISSN 1555-0273, Vol. 19, no 2, p. 155-163Article in journal (Refereed)
  • 47.
    Okwori, Emmanuel
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Analytics-driven approaches supporting asset management of sanitary sewer networks2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Sewer blockages can cause overflows and flooding, with consequences such as damage to property and environmental pollution, risks to public health and economic loss. Despite the causes being understood, blockages in sewer networks may occur unpredictably. The responsible staff for sewer networks at water utilities need to efficiently determine the most effective action (what), the specific network location needing attention (where), the optimal timing for intervention (when), and the appropriate remedial task (how), especially given the unpredictability of blockages. Today a reactive approach to asset management and maintenance is often adopted. Additionally, data availability, quality and interoperability between systems are not always at levels that can support decided objectives, proactive maintenance planning and asset management of pipe networks. Thus, the aim of this thesis is to propose and evaluate approaches that can support analytics-driven maintenance planning and asset management for sewer networks. These approaches aim to contribute to mitigating the impact of siloed data structures and enhance the understanding of blockage root causes from a spatial perspective.

    In this thesis, the challenges of data management in the asset management of pipe networks were investigated through focus group workshops and questionnaire surveys. A conceptual framework was developed based on findings from focus group workshops and surveys. The framework combines data quality assessments, interoperability evaluations between asset management tools, data collection, and informational benefits analysis. This framework aimed to identify the presence of data silos and plausible pathways towards more data-driven data management strategies. A performance assessment combining performance indicators associated with blockages and partial least squares regression (PLS) was conducted to draw inferences that could be useful at a strategic level. Furthermore, a spatial heterogeneity assessment of blockages and factors affecting blockages was carried out. This approach combined network kernel density estimation (NKDE), network k-function, and geographically weighted Poisson regression (GWPR). Lastly, a vulnerability assessment was carried out that combined topological analysis using edge-based centrality measures and network cross-k-function. These approaches were applied to three sewer networks.

    The focus group workshops and questionnaire surveys identified several challenges affecting data management in the context of pipe network asset management. Many of the challenges could be ascribed to issues related to data quality and interoperability. Results from the preliminary application of the conceptual framework showed how it could be applied for identifying data silos and pathways to data-driven decision-making towards proactive management blockages in sewers. The observed spatial trends and patterns from network k-function analysis and network kernel density estimation showed spatial variability in the occurrence of blockages (single occurring and recurring). Geographically-weighted Poisson regression analysis showed spatial heterogeneity in factors influencing blockage propensity. The network cross-k-function analysis demonstrated that pipes with historical blockage incidents tend to be clustered around critical pipes with higher centrality values. These results could support vulnerability assessments in sewer networks and the development of targeted maintenance strategies. These approaches together could aid data-informed maintenance planning and asset management at the strategic, tactical and operational levels.

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  • 48.
    Saadat, Nazmus
    et al.
    Centre for Biocomposites and Biomaterials Processing, Division of Forestry, Daniels Faculty of Architecture, Landscape and Design, University of Toronto, Toronto, Ontario, Canada.
    Dias, Otavio Titton
    Centre for Biocomposites and Biomaterials Processing, Division of Forestry, Daniels Faculty of Architecture, Landscape and Design, University of Toronto, Toronto, Ontario, Canada.
    Jaffer, Shaffiq
    Total NA, Hopkinton MA, USA.
    Tjong, Jimi
    Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada.
    Oksman, Kristiina
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada.
    Sain, Mohini
    Centre for Biocomposites and Biomaterials Processing, Division of Forestry, Daniels Faculty of Architecture, Landscape and Design, University of Toronto, Toronto, Ontario, Canada; Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada.
    Anisotropically layered 2D-3D biocarbon-carbon functionality in sustainable high-performance composite for bipolar plates in fuel cell2024In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 224, article id 120155Article in journal (Refereed)
  • 49.
    Wiklund, Viktor
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Knutsson, Roger
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Anrikningssand: - ett  geotekniskt material2024In: Bygg och Teknik, ISSN 0281-658X, E-ISSN 2002-8350, no 1, p. 15-18Article in journal (Other (popular science, discussion, etc.))
    Abstract [sv]

    Vid Luleå tekniska universitet sker forskning kring anrikningssandoch gruvdammar. Vid bedömning av gruvdammars stabilitet är ConePenetration Test (CPT) en vanligt förekommande metod. I ett pågåendeprojekt tillverkas nu en kalibreringskammare där CPT kan utföras i jordmed fullt kontrollerade förhållanden. Forskningsresultatet kommer geoss bättre utvärderingsmetoder vid analys av CPT-resultat.

  • 50.
    Parihar, Hrithik
    et al.
    School of Mechanical Engineering (SMEC), Vellore Institute of Technology Chennai Campus, Vandalur Kelambakkam Road, Chennai-600127, India.
    Venkatesh, Naveen
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. School of Mechanical Engineering (SMEC), Vellore Institute of Technology Chennai Campus, Vandalur Kelambakkam Road, Chennai-600127, India.
    Anoop, P S
    School of Mechanical Engineering (SMEC), Vellore Institute of Technology Chennai Campus, Vandalur Kelambakkam Road, Chennai-600127, India; Sustainable Mobility Automobile Research Technology (SMART) Center,Dept. of Electronics and Communication Engineering,Amrita Vishwa Vidyapeetham, Amritapuri, India.
    Sugumaran, V
    School of Mechanical Engineering (SMEC), Vellore Institute of Technology Chennai Campus, Vandalur Kelambakkam Road, Chennai-600127, India.
    Application of feature fusion strategy for monitoring the condition of nitrogen filled tires using tree family of classifiers2024In: Physica Scripta, ISSN 0031-8949, E-ISSN 1402-4896, Vol. 99, no 3, article id 035210Article in journal (Refereed)
    Abstract [en]

    The tire pressure monitoring systems(TPMS) are dedicated vehicle systems that calculate the tirepressure under various conditions. Proper maintenance of tire pressure can have a significant impacton enhancing vehicle handling, vehicle performance, occupant safety, comfort and fuel efficiency.Recent years have seen a shift in the preference for nitrogen-filled tires over air filled due to thesuperior thermal stability and uniform pressure management characteristics displayed by nitrogenfilled tires. The present article details the application of machine learning in TPMS to provide moreinsights into the tire behaviour for four different tire conditions(puncture, idle, high and normal).This paper specifically focuses on the collaborative approach that combines various features extractedwith tree-based classifiers. Vertical wheel hub vibrations were captured using an accelerometer fromwhich distinct features like autoregressive moving average (ARMA), statistical and histogram wereextracted. With the application of J48, the most significant and contributing features were identifiedfor every feature set extracted that was fed into tree-based classifiers. The best-performing classifier forevery feature set was determined to be 95.83% (statistical–random forest), 93.75% (histogramoptimized forest) and 93.75% (ARMA–random forest). Furthermore, an extensive analysis wascarried out to determine the impact of the feature fusion approach on feature combinations likestatistical-histogram, histogram-ARMA, statistical-ARMA and statistical-histogram-ARMA. Theexperimental results indicate a commendable classification accuracy of 97.92% for a feature fusion ofstatistical-histogram-ARMA features with a forest penalizing attributes algorithm.

    The full text will be freely available from 2026-02-14 15:09
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