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
Gender bias in lending-based crowdfunding : the case of technology development projects
(2026-08-23) Eriksson, Victoria; Ek, Kristina; Lazarczyk Carlson, Ewa; Söderholm, Patrik; Department of Business and Economics
The purpose of the paper is to investigate whether lending crowdfunding offers equal opportunities for female and male entrepreneurs in the context of a technology demonstration project. The analysis recognises the potential role of signalling, i.e. suggesting that any success in attracting funding may not only be contingent on gender per se, but also on how signals from women and men concerning the various project attributes will be interpreted. We design a split-sample discrete choice experiment that, apart from financial factors, consider two quality signals: private co-funding and downstream actor collaboration. Data are collected through a survey of over 2000 Swedish individuals and analysed using mixed logit models. Overall, the results indicate little gender bias against women in the case of a (characteristically) male-dominated technological development project. We find very limited evidence suggesting that any of the two project quality signals are perceived differently based on the project owner’s gender. Still, the results show that male lenders place a larger premium on actor collaboration when the project owner is female. On the whole, our findings indicate that lending crowdfunding could potentially help democratize the access to capital and reduce any existing funding obstacles for women.
Defining collectivism as duties in relationships rather than generalized warmth improves predictive validity in 100 cultures
(2026-09-15) The Responsibilism Collaboration Team; Department of Business and Economics
Experts widely agree that East Asian cultures are more collectivistic than Western cultures. Yet 76 survey studies found no reliable difference. Our explanation is that the most-used surveys are contaminated with ‘warm fuzzy’ items, which describe warmth and prosociality towards everyone near and far. We argue that collectivism is better understood as ‘responsibilism’, which emphasizes responsibilities in close relationships. A survey found that many cultural psychologists expect collectivistic cultures to agree with warm fuzzy items. Then we developed a responsibilism scale and tested 12,247 people in 100 cultures. Results showed large cultural differences (d = 3.98 [2.50, 5.43]) that were previously obscured by flawed measurement. Responsibilism predicted differences across societies (such as family ties and corruption) and individuals (social class and politics) that most earlier scales missed. This study offers a solution to previous puzzling findings by distinguishing warm fuzzy prosociality from responsibilism and introducing a scale with stronger predictive validity.
Cortical Network Overconnectivity Relates to Sensory, Cognitive, and Social Dimensions in Young Children With Autism Spectrum Disorder
(2026-09) Rodríguez-Herreros, Borja; Mheich, Ahmad; Osório, Joana Maria Almeida; Richetin, Sonia; Junod, Vincent; Arnold, Lorène; Aeschbach, Victoria; Adamou, Lilia Nora; Gschwend, Katherina; Mendes, Laura; Romascano, David; Yu, Paola; Gygax, Marine Jequier; Maillard, Anne M.; Murray, Micah M.; Hassan, Mahmoud; Chabane, Nadia
The heterogeneity in both the neurobiological mechanisms and the phenotypic presentations of autism spectrum disorder (ASD) poses a major challenge to clinical and translational research. Alterations in functional connectivity (FC) have been associated with ASD, yet it remains unclear whether and how divergent brain network properties may account for individual differences across ASD-related symptomatology and behaviors. We applied source-level reconstruction to rest-like non-task-related high-density EEG data in a cohort of 104 young children (38 with ASD) to identify global and local alterations of cortical network connectivity. We subsequently used regularized canonical correlation analysis (rCCA) to characterize specific FC patterns linked to variation in cognitive, social and sensory dimensions derived from standard clinical instruments. We found increased low-frequency FC in frontotemporal cross-hemispheric networks and lateral-occipital regions of young ASD children versus healthy peers. RCCA revealed three distinct FC patterns in recurrent ASD-related networks, each contributing to predict individual differences in cognitive, social and sensory features. These linked FC-behavior dimensions may shed light on atypical brain network topology associated with specific phenotypic manifestations of ASD, which might implicate unique underlying neurobiological mechanisms.
Consumer search patterns in online retailing
(2026-06-01) Dreneva, Anna; Orquin, Jacob L.; Department of Business and Economics
Online retailers routinely rely on sorting, filters, and personalized assortments, but the effectiveness of these design choices depends on how consumers search and decide in digital environments. This research develops a unified and behaviorally grounded framework that conceptualizes consumer search as a context-dependent screening process. Using a novel approach that integrates eye-tracking, mouse-scroll behavior, subjective product preferences, and choice data, we analyze sequences of search events across two studies. The findings show that consumers do not follow a single search strategy but instead adapt their search flexibly to product value and context. Search unfolds as an adaptive screening process in which consumers scan many low-value products, examine a smaller set of higher-value options, and compare only a few top candidates before choosing. Moreover, consumers search less when the overall value of seen products is higher. This framework integrates previously disconnected research streams on decision processes, stopping rules, and consideration set formation, and offers actionable guidance for design and decision-support tools in online retailing.
Broad-Range Inverse Design of Antennas Using Deep Neural Networks with Material Parameter Embedding and Rapid Fine-Tuning
(2026-09-01) Koziel, Slawomir; Pietrenko-Dabrowska, Anna; Department of Engineering
Contemporary antenna design increasingly depends on numerical optimization to manage multiple design variables, objectives, and constraints. In many applications, such as metasurfaces, antenna arrays, or redesign over wide operating ranges, global optimization is no longer optional but essential. However, conventional bioinspired algorithms are notoriously inefficient, while machine learning-based methods struggle to construct sufficiently accurate metamodels. This communication presents a new broad-range optimization strategy based on inverse data-driven surrogates implemented with deep convolutional neural networks (CNNs). A custom embedding process is applied to allow constructing models covering diverse material properties (e.g., substrate permittivity). The surrogate maps antenna frequency responses to geometry parameters. Training data are generated in a dimensionally reduced space that captures the most influential directions in the design space, enabling accurate model construction with a limited number of samples. In the first phase, the inverse model produces an initial design directly from the performance specifications (e.g., desired operating bandwidth) mapped into a target frequency response, which is subsequently refined using an accelerated gradient-based optimizer. The presented approach is verified with two planar antennas optimized for the best reflection response and gain. The outcomes indicate that the inverse surrogate can be applied across a broad spectrum of frequencies, geometries, and substrate materials at a low cost of fewer than 30 electromagnetic (EM) analyses on average. Benchmarking demonstrates the benefits of our method and its practical edge over a broad spectrum of bioinspired, machine learning (ML), and surrogate-assisted population-based approaches.
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