| 1. |
- Mota-Babiloni, A., et al.
(författare)
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Experimental exergy analysis of R513A to replace R134a in a small capacity refrigeration system
- 2018
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Ingår i: Energy. - : Elsevier Ltd. - 0360-5442 .- 1873-6785. ; 162, s. 99-110
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Tidskriftsartikel (refereegranskat)abstract
- The replacement of HFCs using lower GWP refrigerants in the coming years is a priority to reduce the predicted climate change. The exergy analysis of vapor compression systems can help to identify the feasibility of alternative fluids in existing installations and the potential to improve them. In this sense, this paper presents an exergy analysis of an experimental setup which operates with R134a and the alternative HFO/HFC mixture R513A. The evaporating temperature is ranges between −15 °C and 5 °C, while the condensing temperature is set at 30 °C and 35 °C. In this analysis, the highest amount of exergy destruction rate is obtained at the compressor, followed by the evaporator. The maximum exergy efficiencies are observed at the condenser and the thermostatic expansion device. Finally, the average global exergy efficiency of R513A when replaced R134a in this refrigeration experimental setup is 0.4% higher (absolute difference), and with respect to the components, there is only slight reduction in efficiency in the condenser using R513A. Therefore, the R513A replacement is acceptable according to the second law of thermodynamics.
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| 2. |
- Buckley, Jeffrey, 1992-, et al.
(författare)
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An assessment of the transparency of contemporary technology education research employing interview-based methodologies
- 2021
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Ingår i: International journal of technology and design education. - : Springer Nature. - 0957-7572 .- 1573-1804.
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Tidskriftsartikel (refereegranskat)abstract
- A high level of transparency in reported research is critical for several reasons, such as ensuring an acceptable level of trustworthiness and enabling replication. Transparency in qualitative research permits the identification of specific circumstances which are associated with findings and observations. Thus, transparency is important for the repeatability of original studies and for explorations of the transferability of original findings. There has been no investigation into levels of transparency in reported technology education research to date. With a position that increasing transparency would be beneficial, this article presents an analysis of levels of transparency in contemporary technology education research studies which employed interviews within their methodologies, and which were published within the International Journal of Technology and Design Education and Design and Technology Education: An International Journal (n = 38). The results indicate room for improvement, especially in terms of documenting researcher positionality, determinations of data saturation, and how power imbalances were managed. A discussion is presented on why it is important to improve levels of transparency in reported studies, and a guide on areas to make transparent is presented for qualitative and quantitative research.
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| 3. |
- Dartora, Caroline, et al.
(författare)
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A deep learning model for brain age prediction using minimally preprocessed T1w images as input
- 2023
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Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media SA. - 1663-4365 .- 1663-4365. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: In the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We developed and validated a convolutional neural network (CNN)-based biological brain age prediction model that uses one T1w MRI preprocessing step when applying the model to external datasets to simplify implementation and increase accessibility in research settings. Our model only requires rigid image registration to the MNI space, which is an advantage compared to previous methods that require more preprocessing steps, such as feature extraction. Methods: We used a multicohort dataset of cognitively healthy individuals (age range = 32.0–95.7 years) comprising 17,296 MRIs for training and evaluation. We compared our model using hold-out (CNN1) and cross-validation (CNN2–4) approaches. To verify generalisability, we used two external datasets with different populations and MRI scan characteristics to evaluate the model. To demonstrate its usability, we included the external dataset’s images in the cross-validation training (CNN3). To ensure that our model used only the brain signal on the image, we also predicted brain age using skull-stripped images (CNN4). Results: The trained models achieved a mean absolute error of 2.99, 2.67, 2.67, and 3.08 years for CNN1–4, respectively. The model’s performance in the external dataset was in the typical range of mean absolute error (MAE) found in the literature for testing sets. Adding the external dataset to the training set (CNN3), overall, MAE is unaffected, but individual cohort MAE improves (5.63–2.25 years). Salience maps of predictions reveal that periventricular, temporal, and insular regions are the most important for age prediction. Discussion: We provide indicators for using biological (predicted) brain age as a metric for age correction in neuroimaging studies as an alternative to the traditional chronological age. In conclusion, using different approaches, our CNN-based model showed good performance using one T1w brain MRI preprocessing step. The proposed CNN model is made publicly available for the research community to be easily implemented and used to study ageing and age-related disorders.
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| 4. |
- Laure, Erwin, et al.
(författare)
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Programming the Grid using gLite
- 2006
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Ingår i: Computational Methods in Science and Technology. - 1505-0602. ; 12:1, s. 33-45
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The past few years have seen the creation of the first production level Grid infrastructures that offer their users a dependableservice at an unprecedented scale. Depending on the flavor of middleware services these infrastructures deploy (for instance Condor,gLite, Globus, UNICORE, to name only a few) different interfaces to program the Grid infrastructures are provided. Despite ongoingefforts to standardize Grid service interfaces, there are still significant differences in how applications can interface to a Grid infrastructure.In this paper we describe the middleware (gLite) and services deployed on the EGEE Grid infrastructure and explain how applicationscan interface to them.
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| 5. |
- Laure, Erwin, et al.
(författare)
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Programming the grid with glite
- 2006
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Ingår i: Computational Methods in Science and Technology. - 1505-0602. ; 12:1, s. 33-45
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The past few years have seen the creation of the first production level Grid infrastructures that offer their users a dependable service at an unprecedented scale. Depending on the flavor of middleware services these infrastructures deploy (for instance Condor, gLite, Globus, UNICORE, to name only a few) different interfaces to program the Grid infrastructures are provided. Despite ongoing efforts to standardize Grid service interfaces, there are still significant differences in how applications can interface to a Grid infrastructure. In this paper we describe the middleware (gLite) and services deployed on the EGEE Grid infrastructure and explain how applications can interface to them.
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