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.
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Pre-trained deep learning space mapping with intermittent model enhancement for fast multi-fidelity microwave design optimization
(2026-09-14) Koziel, Slawomir; Pietrenko-Dabrowska, Anna; Department of Engineering
Parameter tuning is essential in the development of microwave devices. In recent years, a growing interest in formal optimization methods has emerged, driven by their ability to simultaneously adjust multiple decision variables, even under constraints. Their disadvantage is their high computational cost, which is a serious obstacle to the optimization of electromagnetic (EM) models. This difficulty can be alleviated using multi-fidelity simulations. Problem-independent approaches rely on low-fidelity models constructed through coarse-discretization EM analysis (in contrast to problem-specific equivalent network representations), where a critical factor is the appropriate model correction strategy. This paper introduces a versatile deep-learning space mapping (DLSM) strategy that leverages a reusable pre-trained neural network surrogate. The non-parametric DLSM model implements multi-point response correction, applied independently to the real and imaginary components of relevant S-parameter responses. Furthermore, it is trained as a function of the problem's decision variables and response interrelations. It is embedded in a gradient-based optimization loop, where it is locally retrained using intermittent high-fidelity simulations and sample weighting to place greater emphasis on the neighborhood of the current solution. Comprehensive verification of the procedure involving three planar circuits underscores its competitive efficacy, with a mean running cost of 16 high-fidelity simulations and relative savings over the baseline algorithm up to 87%. Meanwhile, consistent results obtained for multiple scenarios targeting diverse performance specifications corroborate DLSM reusability and applicability across broad ranges of operating conditions.
What Static Connectivity Misses : Dynamic Alpha-Band Brain Network States in First-Episode Psychosis
(2026-09-11) Aubonnet, Romain; Hassan, Mahmoud; Gargiulo, Paolo; Seri, Stefano; Di Lorenzo, Giorgio; Department of Engineering
This study investigates resting-state EEG alpha-band connectivity in first-episode psychosis (FEP) using a novel dynamic connectivity pipeline and examines its relationship with cognitive functioning and psychopathological scores. Data from 78 individuals with FEP and 60 healthy controls (CTR) were analyzed. Source estimation was performed using eLORETA, and connectivity was quantified with the weighted phase-lag index. Static connectivity matrices were assessed using graph theory and edge-wise metrics. Dynamic connectivity matrices were clustered into five distinct brain network states (BNS) using a modified k-means algorithm, from which temporal and graph theory metrics were extracted. Static connectivity metrics revealed lower alpha connectivity in FEP than in controls. The dynamic approach identified reduced variability in the characteristic path length within the default mode network–associated BNS 1 in FEP, suggesting diminished adaptive modulation of functional integration. Subgroup analysis by medication status uncovered distinct BNS signatures for medicated and unmedicated FEP. BNS metrics were correlated with social cognition measures in CTR and with positive formal thought disorder in FEP, whereas static metrics showed no such associations. These findings suggest that relative to static connectivity metrics, dynamic connectivity provides non-redundant information and underscores the impact of medication on neural dynamics in psychosis.
Public perceptions of gambling in the UK Armed Forces : understanding stigma via qualitative inquiry
(2026-09-09) Smith, Jessica; Treacy, Samantha; Dymond, Simon; Torrance, Jamie; Department of Psychology
Background: Existing research has identified elevated public stigma toward Armed Forces personnel experiencing gambling-related harm. However, the reasoning underlying these perceptions remains poorly understood. Qualitative research can explore the drivers of such stigma and inform potential approaches to reduce it. Methods: A qualitative online survey was conducted with UK-based civilian respondents (N = 52) recruited via Prolific. Participants were screened to ensure they could meaningfully discuss gambling and military life. Open-ended questions invited participants to reflect on perceived risks and discuss attitudes toward gambling in both military and civilian contexts. Responses were analyzed using thematic analysis. Results: Four overarching themes with eleven sub-themes were identified: (1) Constructing the Unknown, (2) Perceived Drivers of Gambling within Military Culture, (3) Locating Responsibility and (4) Responding to Military Gambling. Conclusion: Findings suggest that public interpretations of military gambling-related harm were shaped by tensions between gambling and an idealized military identity, alongside negotiated understandings of responsibility across individual, institutional, and societal levels.
Motivators of Sexual Violence Disclosures and Mental Health : A Mixed Methods Investigation
(2026-09-04) Sigurvinsdottir, Rannveig; Thorvaldsdóttir, Karen Birna; Jónsdóttir, Erla Katrín; Ásgeirsdóttir, Bryndís Björk; Department of Psychology
The aim of this mixed methods study was to examine motivators and characteristics of sexual violence disclosures and relationships with mental health. A representative national sample of male and female Icelandic adult survivors (N = 473) took part in a survey. Disclosure was common, especially among women, and psychological symptoms were greatest among late disclosers. Motivators of disclosure included violence itself, trauma and recovery, and social context and movements. Social context and movements disclosures related to lower psychological symptoms. Further research is needed to understand how disclosing related to social movements, such as #MeToo, could potentially confer mental health benefits.
Temporal dynamics of EEG microstates during postural control in Parkinson's disease
(2026-09-01) Gelormini, Carmine; Guerrini, Lorena; Pescaglia, Federica; Maruotto, Ida; Aubonnet, Romain; Jónsson, Halldór; Petersen, Hannes; þormar, Gylfi Örn; Di Lorenzo, Giorgio; Hassan, Mahmoud; Gargiulo, Paolo; Department of Engineering
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterised by motor impairments extending to balance and postural regulation. Although EEG abnormalities in oscillatory activity and functional connectivity are well documented in PD, large-scale brain dynamics during tasks directly engaging postural control remain poorly understood. To address this gap, we examined EEG microstate organisation during the BioVRSea virtual-reality postural-control task in early-stage PD patients (n = 30) and matched healthy controls (HC; n = 26). EEG microstates, brief quasi-stable scalp topographies representing global neural states, provide a robust framework for characterising the rapid temporal structure of whole-brain activity. Although task-based microstate approaches exist, applications to PD remain limited and largely confined to resting-state research. Topographical analyses revealed pronounced between-group differences in microstates D and E, whose group-averaged maps in PD diverged markedly from canonical configurations. Because these maps were not topographically equivalent between groups, comparisons of temporal parameters were restricted to the comparable microstates A–C. Across all task phases, PD patients showed increased duration and coverage of microstates A and B. Transition-probability analysis, likewise restricted to A–C, indicated different trajectories across phases in PD and HC. A single significant Group × Phase interaction emerged for A→C: the largest between-group difference occurred during the POST-movement phase, when PD showed a higher probability than HC. For the remaining transitions, no phase-dependent differences emerged within PD. Because patients were assessed ON medication and clinical or behavioural correlates were unavailable, these findings represent candidate task-state EEG microstate alterations requiring validation, rather than established disease-specific markers.
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