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
Design-ready farfield pattern modeling of broadband antennas using multi-branch attention-based recurrent convolutional decoder neural network
(2027-01) Koziel, Slawomir; Sahu, Kaustab C.; Pietrenko-Dabrowska, Anna; Department of Engineering
Behavioral modeling is becoming increasingly important in antenna development, particularly in accelerating simulation-based design processes such as optimization. However, the construction of accurate data-driven models remains a challenging task, typically limited to electrical responses such as reflection coefficients or integral performance metrics (e.g., gain). In contrast, the behavioral modeling of radiation patterns—although crucial from a design perspective—has been relatively scarce in the existing literature. This research introduces a new surrogate modeling framework for broadband antennas that leverages customized deep learning techniques. The proposed approach enables accurate and comprehensive modeling of both electrical responses (e.g., reflection coefficient, gain) and far-field radiation patterns across a broad range of frequencies, elevation/azimuth angles, and geometric parameters. As a result, the developed surrogates are highly versatile and applicable for addressing a wide spectrum of design and optimization tasks. For accurate representation of radiation patterns, a hybrid deep learning architecture is developed that integrates multi-branch recurrent processing with cross-attention–based feature fusion. Six independent RNN branches (each combining FC, LSTM, and GRU layers) extract complementary representations of the geometric input space, which are subsequently fused through a cascade of attention modules. The fused embedding is decoded using a transposed-convolutional refinement network to reconstruct the full radiation pattern. Extensive validation studies, performed using two ultra-wideband antenna designs, confirm the excellent predictive accuracy and robustness of the proposed surrogates. The results also demonstrate their advantages over multiple benchmark methods, including conventional regression models and various deep learning schemes. Furthermore, the practical utility of the framework is demonstrated through real-world design tasks, including impedance matching enhancement, size reduction, omnidirectional radiation, and gain stability. Overall, the presented methodology represents a significant advancement toward comprehensive multi-response antenna modeling and substantially extends the capabilities of behavioral metamodeling in contemporary antenna design practice.
Optimizing SiGe–SiO2 Visible–Short‐Wave Infrared Photoresponse by Modulating Interplay Between Strain and Defects Through Annealing
(2024-08) Sultan, Muhammad Taha; Stavarache, Ionel; Manolescu, Andrei; Arnalds, Unnar Bjarni; Teodorescu, Valentin Serban; Svavarsson, Halldor Gudfinnur; Ingvarsson, Snorri; Ciurea, Magdalena Lidia; Verkfræðideild
ENLIGHT : A consensus checklist for reporting laboratory-based studies on the non-visual effects of light in humans
(2023-12) ENLIGHT Consortium; Department of Psychology
Background: There is no consensus on reporting light characteristics in studies investigating non-visual responses to light. This project aimed to develop a reporting checklist for laboratory-based investigations on the impact of light on non-visual physiology. Methods: A four-step modified Delphi process (three questionnaire-based feedback rounds and one face-to-face group discussion) involving international experts was conducted to reach consensus on the items to be included in the checklist. Following the consensus process, the resulting checklist was tested in a pilot phase with independent experts. Findings: An initial list of 61 items related to reporting light-based interventions was condensed to a final checklist containing 25 items, based upon consensus among experts (final n = 60). Nine items were deemed necessary to report regardless of research question or context. A description of each item is provided in the accompanying Explanation and Elaboration (E&E) document. The independent pilot testing phase led to minor textual clarifications in the checklist and E&E document. Interpretation: The ENLIGHT Checklist is the first consensus-based checklist for documenting and reporting ocular light-based interventions for human studies. The implementation of the checklist will enhance the impact of light-based research by ensuring comprehensive documentation, enhancing reproducibility, and enabling data aggregation across studies. Funding: Network of European Institutes for Advanced Study (NETIAS) Constructive Advanced Thinking (CAT) programme; Sir Henry Wellcome Postdoctoral Fellowship (Wellcome Trust, 204686/Z/16/Z); Netherlands Organisation for Health Research and Development VENI fellowship (2020–09150161910128); U.S. Department of Defense Grant (W81XWH-16-1-0223); National University of Singapore (NUHSRO/2022/038/Startup/08); and National Research Foundation Singapore (NRF2022-THE004-0002).
Neurocognitive function and health-related quality of life in a nationwide cohort of long-term childhood brain tumor survivors
(2023-04-01) Helligsoe, Anne Sophie L.; Henriksen, Louise T.; Kenborg, Line; Lassen-Ramshad, Yasmin; Wu, Lisa M.; Winther, Jeanette F.; Hasle, Henrik; Amidi, Ali; Department of Psychology
Background. Childhood brain tumor survivors are at high risk of late effects, especially neurocognitive impairment. Limited data are available examining neurocognitive function and associations with quality of life (QoL) in childhood brain tumor survivors. Our aim was to examine neurocognitive function in childhood brain tumor survivors, and associations with QoL and symptom burden. Methods. Five–year survivors of brain tumors over the age of 15 were identified in the Danish Childhood Cancer Registry (n = 423). Eligible and consenting participants completed neuropsychological tests and questionnaires assessing QoL, insomnia, fatigue, anxiety, and depression. Survivors treated with radiation (n = 59) were statistically compared with survivors not treated with radiation (n = 102). Results. In total, 170 survivors participated (40.2% participation rate). Sixty-six percent of the survivors who completed neurocognitive tests (n = 161) exhibited overall neurocognitive impairment. Survivors treated with radiation, especially whole-brain irradiation, exhibited poorer neurocognitive outcomes than survivors not treated with radiation. Neurocognitive outcomes for survivors treated with surgery were below normative expectations. Furthermore, a number of survivors experienced significant fatigue (40%), anxiety (23%), insomnia (13%), and/or depression (6%). Survivors treated with radiation reported lower quality of life (QoL) and higher symptom burden scores than survivors not treated with radiation; particularly in physical functioning, and social functioning with symptoms of fatigue. Neurocognitive impairment was not associated with QoL or symptom burden. Conclusions. In this study, a majority of the childhood brain tumor survivors experienced neurocognitive impairment, reduced QoL, and high symptom burden. Although not associated with each other, it is apparent that childhood brain tumor survivors experience not only neurocognitive dysfunction but may also experience QoL impairments and significant symptom burden.
Optimizing a Behavioral Sleep Intervention for Gynecologic Cancer Survivors : Study Design and Protocol
(2022-03-04) Fox, Rina S.; Gaumond, Julia S.; Zee, Phyllis C.; Kaiser, Karen; Tanner, Edward J.; Ancoli-Israel, Sonia; Siddique, Juned; Penedo, Frank J.; Wu, Lisa M.; Reid, Kathryn J.; Parthasarathy, Sairam; Badger, Terry A.; Rini, Christine; Ong, Jason C.; Department of Psychology
Sleep difficulties, particularly symptoms of insomnia and circadian disruption, are among the primary complaints of gynecologic cancer survivors before, during, and after treatment. Moreover, difficulty sleeping has been linked to poorer health-related quality of life and elevated symptom burden in this population. Although leading behavioral sleep interventions have demonstrated efficacy among cancer survivors, up to 50% of survivors are non-adherent to these treatments, likely because these interventions require labor-intensive behavior and lifestyle changes. Therefore, there is a need for more effective and acceptable approaches to diminish sleep disturbance among cancer survivors. This manuscript describes the methodology of a two-part study guided by the Multiphase Optimization Strategy (MOST) framework to identify a streamlined behavioral sleep intervention for gynecologic cancer survivors. Three candidate intervention components previously shown to decrease sleep disturbance will be evaluated, including sleep restriction, stimulus control, and systematic bright light exposure. Participants will be adult women with a history of non-metastatic gynecologic cancer who have completed primary treatment and who report current poor sleep quality. Fifteen participants will be recruited for Part 1 of the study, which will utilize qualitative methods to identify barriers to and facilitators of intervention adherence. Results will inform changes to the delivery of the candidate intervention components to promote adherence in Part 2, where 80 participants will be recruited and randomized to one of eight conditions reflecting every possible combination of the three candidate intervention components in a full factorial design. Participants will complete assessments at baseline, post-intervention, and 3-months post-intervention. Part 2 results will identify the combination of candidate intervention components that yields the most efficacious yet efficient 6-week intervention for diminishing sleep disturbance. This is the first known study to apply the MOST framework to optimize a behavioral sleep intervention and will yield a resource-efficient treatment to diminish sleep disturbance, improve health-related quality of life, and decrease symptom burden among gynecologic cancer survivors. ClinicalTrials.gov Identifier: NCT05044975.
Flokkar í Opnum vísindum
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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