Opin vísindi
Opin vísindi er varðveislusafn vísindaefnis og doktorsritgerða í opnum aðgangi á vegum íslenskra háskóla og Landsbókasafns Íslands - Háskólabókasafns.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Nýlega bætt við
Scale-free to Pareto–Tsallis transitions in the distributions of waiting times : weather, sea-level, currency trading and automotive datasets
(2026-09) Gogîţă, Paul Adrian; Dumitru, Tudor Gabriel; Constantin, Florin Ioan; Diac, Tudor Andrei; Neagoe, Alexandra Florentina; Raportaru, Mihaela Carina; Nicolin-Żaczek, Alexandru; Department of Engineering
We report a series of detailed statistical analyses on the distributions of waiting times pertaining to a diverse set of complex systems, including terrestrial and space weather, sea-level variations, currency trading (for both fiat and cryptocurrencies), and synthetic automotive data. Given a generic time series, we define a waiting time as the shortest time interval needed to find an entry of value of at least (Formula presented) (Formula presented), with (Formula presented) (Formula presented) a given threshold, after a certain entry of value (Formula presented) (Formula presented) was observed. Going through the entire time series we obtain the complete set of waiting times for a specific value of (Formula presented) (Formula presented) and can determine their distribution. This distribution can be seen as a dynamic fingerprint of the process to which the time series pertains and is particularly useful to directly compare the dynamics of otherwise very different systems. To this end, we show that the aforementioned distributions have a prominent scale-free character for small values of (Formula presented) (Formula presented) for all datasets under scrutiny, while for large values of (Formula presented) (Formula presented) the observed distributions of waiting times converge to a Pareto–Tsallis distribution. We identify the threshold values (Formula presented) (Formula presented) at which this transition occurs using the goodness-of-fit indicators, and further substantiate these results by analyzing the behavior of the generalized Kullback–Leibler divergence. Our results are robust across all of the considered datasets.
Oxygen Field Dynamics in Bioconvection and the Spatial Organization of Multispecies Aerobic Bacteria
(2026-07-01) Gallardo-Navarro, Oscar; Arbel-Goren, Rinat; Dassa, Bareket; August, Elias; Stavans, Joel; Department of Engineering
Emergent self-organization is a hallmark of natural bacterial communities, whose spatial structures and dynamic gradients are shaped by the complex interplay among bacterial diversity, oxygen and its consumption, and motility and by hydrodynamic flows. Key aspects of the interplay between oxygen gradients and bacterial community spatial structure remain obscure. Here we aim to elucidate the role that oxygen plays in the self-organization of multispecies bacteria in the water column, focusing on oxytactic bioconvection suspensions of naturally coexisting aerobic bacteria and on self-organization near air-water interfaces. Combining microscopy, mapping of the oxygen field and controlled external oxygen levels, we show that species-specific oxygen affinities and consumption rates induce the formation of distinct bacterial layers near air-water interfaces, resulting in dynamic segregation during multispecies bioconvection, and play a key role in determining the nature of bioconvective patterns in single species suspensions. We further find that oxygen and bacterial fields are tightly coupled and fluctuate with similar spatiotemporal scales, giving rise to oxygen advection and a well-defined oxic-anoxic boundary. Together, our results illuminate the fundamental role that oxygen gradients play in multispecies bacterial active matter and its spatial self-organization, with implications for the formation and stability of ecological niches in aquatic and sedimentary environments.
Objective stratification of knee osteoarthritis stages using a semi-supervised learning approach on multimodal MRI-CT cartilage features
(2026-06-25) Ciliberti, Federica Kiyomi; Maruotto, Ida; Jonsson, Halldor; Gargiulo, Paolo; Department of Engineering
Introduction – Knee osteoarthritis (KOA) is a chronic and progressive joint disease that affects middle-aged and older adults. Early detection is crucial to prevent progression toward joint replacement and improve long-term outcomes, yet current diagnoses are strongly influenced by subjective symptoms, especially pain perception, which varies widely across individuals and does not reliably reflect structural degeneration. This study introduces a semi-supervised learning (SSL) framework for characterizing KOA stages through combined MRI and CT-derived cartilage features. Methods – A cohort of 133 knee scans was analyzed, including 36 expert-labeled cases categorized as healthy, early degeneration, or advanced degeneration. These labels served as seeds for graph-based SSL using Label Propagation and Label Spreading, producing pseudo-labels for the remaining samples. Results – Label stability across ten Monte Carlo runs demonstrated high agreement (0.91 (Formula presented) 0.14) and substantial reliability (Fleiss’ kappa = 0.781). Supervised classifiers trained on the SSL-labeled dataset achieved robust performance, with Support Vector Machines and Logistic Regression yielding the highest weighted F1-scores (0.84 and 0.81, respectively). Statistical analysis confirmed significant differences among the three classes for all extracted features. Discussion – The volume-to-surface ratio and density heterogeneity demonstrated the strongest discriminatory power, reflecting progressive cartilage thinning, surface irregularity, and increasing structural heterogeneity consistent with KOA pathophysiology. These results show that combining expert knowledge with SSL enables reliable KOA stratification even with limited labeled data, offering meaningful insights into cartilage degeneration and laying the foundation for quantitative and more objective imaging-based biomarkers and future continuous scoring systems.
Experimentally validated dual-band GHz metamaterial perfect absorber biosensor with negative-index response and AI-assisted electromagnetic analysis for breast cancer dielectric discrimination
(2026-06-25) Hamza, Musa N.; Islam, Mohammad Tariqul; Koziel, Slawomir; Alibakhshikenari, Mohammad; Virdee, Bal; Mariyanayagam, Dion; Lavadiya, Sunil; Din, Iftikhar ud; Sanches, Bruno; Naqvi, Syeda Iffat; Panda, Abinash; Farmani, Ali; Mezache, Zinelabiddine; Shamsan, Zaid Ahmed; Farmani, Homa; Ghafourivayghan, Mahdi; Chaudhary, Muhammad Akmal; Naser-Moghadasi, Mohammad; Islam, Md Shabiul; Department of Engineering
A dual-band GHz metamaterial absorber (MPA) biosensor is presented as a proof-of-concept platform for dielectric-sensitive electromagnetic sensing integrated with AI-assisted broadband spectral analysis. The proposed three-layer copper–FR-4–copper structure exhibits near-unity absorption at 6.0 GHz and 9.1 GHz and demonstrates engineered negative-index behavior, which enhances electromagnetic field confinement and sensitivity to dielectric perturbations. The biosensor was fabricated using standard PCB technology and experimentally validated through free-space microwave measurements, showing excellent agreement with simulations and absorption exceeding 92.5% and 99.8% at the two resonant frequencies. For dielectric-sensitive analysis, the sensor response was evaluated under simulation-based loading conditions using low-loss COC/COP coverslip layers and literature-reported electromagnetic properties representative of healthy-like and malignant-like breast environments. Distinct broadband spectral perturbations were observed across the 5–10 GHz frequency range, demonstrating sensitivity to dielectric-property variations. Sensor performance was assessed using quality factor, sensitivity, and figure-of-merit metrics. An AI-assisted spectral interpretation framework was developed using distance- and correlation-based analysis of the broadband electromagnetic response. The results demonstrate that the proposed platform combines dual-band high-Q absorption, engineered triple-negative electromagnetic characteristics, and AI-assisted spectral analysis within a unified microwave biosensing framework. No biological samples were evaluated in this study; therefore, the reported results should be interpreted as simulation-based dielectric-loading analyses rather than validated cancer-detection outcomes.
Association of major adverse cardiovascular events with the apnea-hypopnea index, desaturation severity parameters, and cardiac troponins in participants of the Akershus Sleep APnea cohort
(2026-08) Feng, Xin; Sigurdardottir, Fjola; Arnardottir, Erna Sif; Dammen, Toril; Einvik, Gunnar; Korkalainen, Henri; Klungsøyr, Ole; Leppänen, Timo; Nordhus, Inger Hilde; Nikkonen, Sami; Töyräs, Juha; Thorshov, Thea; Øverby, Tonje Caroline; Omland, Torbjørn; Hrubos-Strøm, Harald; Department of Engineering
Study Objectives: To examine the prognostic value of the apnea-hypopnea index (AHI), desaturation severity parameters, and cardiac troponins alone and combined for major cardiovascular events (MACEs). Methods: MACE data were retrieved in 2021 from the Norwegian Patient Registry for 518 participants in the Akershus Sleep APnea (ASAP) cohort. Baseline polysomnography and fasting blood samples were collected between June 2006 and January 2008. Desaturation duration (DesDur) and severity (DesSev) were calculated using Automatic Blood Oxygen Saturation Analysis software. Cox regression models estimated hazard ratios (HRs) for MACE. Predictive properties of combining troponins and obstructive sleep apnea severity were calculated by comparing established clinical thresholds for cardiac troponin I (cTnI) and T (cTnT) with AHI clinical thresholds of ≥15 and ≥30, respectively. Results: High AHI, DesDur, DesSev, cTnI, and cTnT were associated with increased MACE risk. However, only cTnI independently predicted MACE after adjustment (HR: 1.74, 95% CI: 1.32–2.29). The HR for MACE was 2.68 (95% CI: 1.03–6.97) in patients with both high cTnI and AHI ≥30 events/h. Conclusion: In this 15-year follow-up, cTnI was independently associated with risk of MACE, whereas the AHI, desaturation parameters, and cTnT were not independent predictors. cTnI, especially when combined with AHI, was a stronger MACE predictor than cTnT. Provided our findings are validated in clinical obstructive sleep apnea populations, the measurement of cTnI may be considered for cardiovascular risk stratification.
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- University of Iceland
- University of Akureyri
- Bifröst University
- Hólar University College
- IRIS
- Agricultural University of Iceland
- National and University Library of Iceland
- Iceland University of the Arts