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
Compact eucapnic voluntary hyperpnoea apparatus for exercise-induced respiratory disease detection
(2017-05-16) Wang, Lulu; Al-Jumaily, Ahmed; Department of Engineering
Eucapnic voluntary hyperpnoea (EVH) challenge provides objective criteria for exercise-induced asthma (EIA) or exercise-induced bronchoconstriction (EIB), and it was recommended to justify the use of inhaled β2-agonists by athletes for the Olympics. This paper presents the development of a compact and easy-to-use EVH apparatus for assessing EIB in human subjects. The compact apparatus has been validated on human subjects and the results have been compared to the conventional EVH system. Twenty-two swimmers, including eleven healthy subjects and eleven subjects who had been physician-diagnosed with asthma, were recruited from sport and recreation centers throughout Auckland, New Zealand. Each subject performed two EVH challenge tests using the proposed breathing apparatus and the conventional Phillips EVH apparatus on separate days, respectively. Forced expiratory volume in one second (FEV1) was measured before and after the challenges. A reduction in FEV1 of 10% or more was considered positive. Of the eleven subjects who were previously diagnosed with asthma, EIB was present in all subjects (100%) in the compact EVH group, while it was presented in ten subjects (90.91%) in the conventional EVH challenge group. Of the eleven healthy subjects, EIB was present in one subject (4.55%) in the compact EVH group, while it was not present in the conventional EVH group. Experimental results showed that the compact EVH system has potential to become an alternative tool for EIB detection.
Compact Circularly Polarized Monopole Antenna Using Characteristic Mode Analysis
(2023) Peddakrishna, Samineni; Wang, Lulu; Kollipara, Vamshi; Kumar, Jayendra; Department of Engineering
This study aims to design a circularly polarized compact antenna using characteristic mode analysis (CMA). The proposed antenna consists of a substrate with a slotted annular ring-shaped patch and partial ground. The excitation position of the antenna and its optimal dimensions are determined through the analysis of different operation modes with CMA. After that, an optimized antenna is designed, and an antenna prototype is fabricated for validation. The experimental results show that the reflection coefficient achieves a -10dB impedance bandwidth of 6.85 GHz, a 3dB-axial ratio bandwidth of 0.7 GHz, and a peak gain of 3.2 dBi. These characteristics agree with simulations and make the circularly polarized compact antenna suit for C-band and sub-6 GHz 5G wireless applications.
Antibiotic resistance genes, antibiotic residues, and microplastics in influent and effluent wastewater from treatment plants in Norway, Iceland, and Finland
(2025-11-15) Tiwari, Ananda; Jaén-Gil, Adrián; Karavaeva, Anastasia; Gomiero, Alessio; Ásmundsdóttir, Ásta Margrét; Silva, Maria João; Salmivirta, Elisa; Tran, Tam T.; Sarekoski, Anniina; Cook, Jeremy; Lood, Rolf; Pitkänen, Tarja; Krolicka, Adriana; Faculty of Natural Resource Sciences
Monitoring antimicrobial resistance genes (ARGs) in wastewater influents (pre-treatment) and effluents (post-treatment) provides insights into community-level circulation, potential amplification during treatment, and risks associated with gene release into surface waters. Pollutants such as antibiotic residues and microplastics (MPs) may influence ARG dynamics, highlighting the need to assess their dynamics across wastewater environments. In this study, we analyzed ARGs and bacterial communities using Oxford Nanopore (ONP) metagenomics and qPCR in wastewater samples from Mekjarvik (Norway), Reykjavik (Iceland), and Mariehamn (Åland, Finland). Antibiotic residues were quantified via high-performance liquid chromatography (HPLC), and MPs were characterized using micro-fourier transform infrared spectroscopy (μ-FTIR) in Mekjarvik and Reykjavik. Metagenomic analysis identified 193 unique ARGs, with the highest average (±SD) in Reykjavik (66.3 ± 4.1), followed by Mekjarvik (61.3 ± 14.1) and Mariehamn (18.0 ± 2.2). ONP sequencing revealed that many ARGs were plasmid-associated, co-occurring with metal stress genes. Common plasmids were Col440I, IncQ2, and ColRNAI. Mercury-related genes dominated metal stress genes (64.9 %), followed by multimetal (23.7 %) and copper (6.4 %). Of 45 antibiotics screened, only sulfamethoxazole and sulfapyridine were consistently detected. Polyethylene (∼60 %) was the dominant MP type; Reykjavik influent had the highest MP load (8200 MP/m3). While treatment reduced ARGs, antibiotic residues, and larger MPs, it was less effective against fine particles and key ARGs, including carbapenemase- and ESBL-associated genes. Clinically relevant ARGs and potential pathogens (e.g., Acinetobacter baumannii, Pseudomonas aeruginosa) persisted in effluents, highlighting risks to downstream ecosystems. These findings underscore the need for regular monitoring of both influents and effluents to assess treatment performance and safeguard environmental health.
Combining Postural Sway Parameters and Machine Learning to Assess Biomechanical Risk Associated with Load-Lifting Activities
(2025-01) Prisco, Giuseppe; Pirozzi, Maria Agnese; Santone, Antonella; Cesarelli, Mario; Esposito, Fabrizio; Gargiulo, Paolo; Amato, Francesco; Donisi, Leandro; Department of Engineering
Background/Objectives: Long-term work-related musculoskeletal disorders are predominantly influenced by factors such as the duration, intensity, and repetitive nature of load lifting. Although traditional ergonomic assessment tools can be effective, they are often challenging and complex to apply due to the absence of a streamlined, standardized framework. Recently, integrating wearable sensors with artificial intelligence has emerged as a promising approach to effectively monitor and mitigate biomechanical risks. This study aimed to evaluate the potential of machine learning models, trained on postural sway metrics derived from an inertial measurement unit (IMU) placed at the lumbar region, to classify risk levels associated with load lifting based on the Revised NIOSH Lifting Equation. Methods: To compute postural sway parameters, the IMU captured acceleration data in both anteroposterior and mediolateral directions, aligning closely with the body’s center of mass. Eight participants undertook two scenarios, each involving twenty consecutive lifting tasks. Eight machine learning classifiers were tested utilizing two validation strategies, with the Gradient Boost Tree algorithm achieving the highest accuracy and an Area under the ROC Curve of 91.2% and 94.5%, respectively. Additionally, feature importance analysis was conducted to identify the most influential sway parameters and directions. Results: The results indicate that the combination of sway metrics and the Gradient Boost model offers a feasible approach for predicting biomechanical risks in load lifting. Conclusions: Further studies with a broader participant pool and varied lifting conditions could enhance the applicability of this method in occupational ergonomics.
Collaborative Registered Replication of Griskevicius et al. (2010) : Can Pro-environmental Behavior Be Promoted by Priming Status Motivation?
(2025-09-15) Lazarevic, Ljiljana B.; Wagge, Jordan R.; Balci, Busra Bahar; Buchanan, Erin M.; Greene, Nathaniel R.; Folwarczny, Michał; Lazić, Aleksandra; Want, Stephen C.; Lee, Seungyeon; Raddatz, Megan C.; Hehman, Eric; Gentile, Adriana; Petrović, Marija B.; De Luca, Paul; Kelly, Andrew J.; Talbot, Karine; Tobia, Jessica; Chalik, Lisa; Tsoi, Lily; Florence, Joey H.; Weissgerber, Sophia C.; Schouler, Niklas; Buron, Laurianne; Christopherson, Cody D.; Richter, Johanna; Senftner, Karina; Pazda, Adam D.; Allen, Peter J.; Kingston, Francesca; Sigurdsson, Valdimar; Grahe, Jon; Department of Business and Economics
The present study presents the results of a collaborative registered replication of Griskevicius et al. (2010, Experiment 1). As part of the Collaborative Replication and Education Project, 24 student groups from six countries (N = 3,774) investigated whether pro-environmental behavior can be promoted by priming status motives (desires for social status and prestige). This large, multi-site replication showed no evidence to support the hypothesis that hypothetical pro-environmental behavior can be stimulated by having participants read a story designed to prime status motives. We performed several exploratory analyses to investigate whether extension variables (i.e., equating “green” choices with prosocial behavior, political beliefs, sampling methods, location, duration of data collection, and gender) moderated the hypothesized effect of status motives on pro-environmental choices, but these analyses produced null results. One limitation of the study is that most data collection sites did not include a manipulation check, and the one site that did found a much weaker effect (d = 0.32) than the extremely large effect originally reported (d = 3.69). As a result, it remains unclear whether the null result reflects a failure of this specific priming method or a challenge to the underlying theory.
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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