| 1. |
- Giordanetto, Fabrizio, et al.
(author)
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Design of Selective sPLA2-X Inhibitor (-)-2-{2-[Carbamoyl-6-(trifluoromethoxy)-1 H-indol-1-yl]pyridine-2-yl}propanoic Acid
- 2018
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In: ACS Medicinal Chemistry Letters. - : American Chemical Society. - 1948-5875 .- 1948-5875. ; 9:7, s. 600-605
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Journal article (peer-reviewed)abstract
- A lead generation campaign identified indole-based sPLA2-X inhibitors with a promising selectivity profile against other sPLA2 isoforms. Further optimization of sPLA2 selectivity and metabolic stability resulted in the design of (-)-17, a novel, potent, and selective sPLA2-X inhibitor with an exquisite pharmacokinetic profile characterized by high absorption and low clearance, and low toxicological risk. Compound (-)-17 was tested in an ApoE-/- murine model of atherosclerosis to evaluate the effect of reversible, pharmacological sPLA2-X inhibition on atherosclerosis development. Despite being well tolerated and achieving adequate systemic exposure of mechanistic relevance, (-)-17 did not significantly affect circulating lipid and lipoprotein biomarkers and had no effect on coronary function or histological markers of atherosclerosis.
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| 2. |
- Brandao, Miguel, et al.
(author)
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RED, PEF, and EPD: Conflicting rules for determining the carbon footprint of biofuels give unclear signals to fuel producers and customers
- 2022
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In: Frontiers in Climate. - : Frontiers Media SA. - 2624-9553. ; 4
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Journal article (peer-reviewed)abstract
- Biofuel producers and other commodity suppliers are increasingly affected by conflicting rules for life cycle assessment (LCA). They may get multiple requests for LCAs to be used in various contexts, which require the application of different methodological approaches that vary in scope, system boundaries, data demand, and more. This results in increased cost and competence requirements for producers, as well as confusion among other actors including their customers. Differences in methodologies might also lead to various outcomes, conclusions and conflicting guidance regarding which fuels to prioritize or develop. We have analyzed the actual differences when applying three different frameworks: the EU Renewable Energy Directive (RED), the EU framework for Product Environmental Footprints (PEF), and the framework of Environmental Product Declarations (EPD), which have different modeling requirements. We analyzed the methods from a conceptual point of view and also applied the methods to estimate the carbon footprint on a wide range of biofuel production pathways: (i) ethanol from corn, (ii) fatty acid methyl ester (FAME) from rapeseed oil, (iii) biogas from food waste, (iv) hydrogenated vegetable oil (HVO) from rapeseed oil, and (v) HVO from used cooking oil. Results obtained for a specific fuel could differ substantially depending on the framework applied and the assumptions and interpretations made when applying the different frameworks. Particularly, the results are very sensitive to the modeling of waste management when biofuel is produced from waste. Our results indicate a much higher climate impact for, e.g., biogas and HVO produced from used cooking oil when assessed with the PEF framework compared to the other frameworks. This is because PEF assigns at least part of the production of primary materials and energy to the use of recycled material and recovered energy. Developing Category Rules for biofuels for PEF and EPD ought to help clarifying remaining ambiguities.
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| 3. |
- Hooey, Lawrence, et al.
(author)
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Role of ferrous raw materials in the energy efficiency of integrated steelmaking
- 2014
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In: ISIJ International. - : Iron and Steel Institute of Japan. - 0915-1559 .- 1347-5460. ; 54:3, s. 596-604
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Journal article (peer-reviewed)abstract
- The role of ferrous raw materials and iron ore agglomeration in energy consumption of integrated steelmaking has been evaluated using a system-wide model. Four steelplant cases were defined: typical European steelplant with sinterplant; Nordic steelplant with sinterplant; European steelplant with sinter:pellet ratio of 50%, and Nordic steelplant charging pellets and a small amount of briquettes. Energy consumption in the mining system were estimated from published statistics at 150 MJ/t for lump ore and sinter fines, 650 MJ/t for pellets made from magnetite and 1 050 MJ/t for pellets made from hematite. An integrated steelplant model including all major unit operations was used to calculate overall system energy consumption from iron ore mining to hot rolled coil. Adjustments were made accounting for energy benefit of ground granulated blast furnace slag in cement production, energy required for cement production required for briquetting, and excess BF and BOF gas producing electricity in a 32% efficient power plant. The system-wide net adjusted energy in the first three steeplant cases showed marginal improvement with use of high grade sinter fines and decrease of pellet/sinter ratio to 50% compared to typical European case. Nordic steelplant charging pellets and briquettes had a reduction in system-wide energy of 5% to 8% for charging pellets from hematite or magnetite respectively compared to the typical European steelplant charging sinter and pellets made from hematite ore. Replacement of sinter with pellets was mainly responsible for the improvement with smaller contributions from magnetite ore in pelletizing.
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| 7. |
- Twitchen, D.J., et al.
(author)
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High Voltage Single Crystal Diamond Diodes
- 2004
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In: IEEE Transactions on Electron Devices. - 0018-9383 .- 1557-9646. ; 51:5, s. 826-828
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Journal article (peer-reviewed)abstract
- Demonstration of a 2.5-kV diamond diode is provided by electrical measurements using a circular gold Schottky contact, with an area > 1 mm(2), on large area freestanding single-crystal diamond consisting of a thin high purity layer (< 1 X 10(13) [B]/cm(3)) on a thicker heavily boron-doped (> 1 X 10(19) [B]/cm(3)) substrate with an ohmic back contact. The diode structures were fabricated using a microwave-assisted chemical vapor deposition process. The forward properties of the diode show a space charge limited current, with a forward-voltage drop of 2 V and a hole mobility of 4100 +/- 400 cm(2) /Vs at room temperature. For temperatures between 300 K < T < 380 K the mobility show T-312 dependence. This is consistent with acoustic phonon scattering, emphasizing the high purity quality of the top layer in which carrier transport is phonon rather than defect limited.
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| 8. |
- Crocetti, Roberto, et al.
(author)
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Takras avslöjar allvarliga brister
- 2011
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In: Samhällsbyggaren. - 2000-2408. ; :5, s. 22-27
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Journal article (pop. science, debate, etc.)abstract
- SP har etablerat en databas med 180 rasade eller skadade tak. Det framgår, att det var övervägande stål- och träkonstruktioner, som hade rasat. Endast en skadad betongkonstruktion rapporterades. Byggnadernas ålder spänner över cirka 100 år, men 60 % är uppförda från 1980 och framåt. Taken är förhållandevis flacka. Ca 30 % är lantbruksbyggnader. De dominerande rasorsakerna är dimensioneringsfel och utförandefel. Till dimensioneringsfel räknas bl a, att man inte har dimensionerat över huvudtaget, och att man inte har beaktat snöfickor mm. Detta är några av slutsatserna i den utredning, som SP har utfört tillsammans med Skanska, Lunds tekniska högskola och Lantbruksuniversitetet, och som publicerades den 1 juni 2011.
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| 9. |
- Kundu, Swagata, et al.
(author)
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ASE-Net for Segmentation of Post-operative Glioblastoma and Patient-specific Fine-tuning for Segmentation Refinement of Follow-up MRI Scans
- 2024
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In: SN computer science. - : Springer. - 2661-8907. ; 5:106
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Journal article (peer-reviewed)abstract
- Volumetric quantification of tumors is usually done manually by radiologists requiring precious medical time and suffering from inter-observer variability. An automatic tool for accurate volume quantification of post-operative glioblastoma would reduce the workload of radiologists and improve the quality of follow-up monitoring and patient care. This paper deals with the 3-D segmentation of post-operative glioblastoma using channel squeeze and excitation based attention gated network (ASE-Net). The proposed deep neural network has a 3-D encoder and decoder based architecture with channel squeeze and excitation (CSE) blocks and attention blocks. The CSE block reduces the dependency on space information and put more emphasize on the channel information. The attention block suppresses the feature maps of irrelevant background and helps highlighting the relevant feature maps. The Uppsala university data set used has post-operative follow-up MRI scans for fifteen patients. A patient specific fine-tuning approach is used to improve the segmentation results for each patient. ASE-Net is also cross-validated with BraTS-2021 data set. The mean dice score of five-fold cross validation results with BraTS-2021 data set for enhanced tumor is 0.8244. The proposed network outperforms the competing networks like U-Net, Attention U-Net and Res U-Net. On the Uppsala University glioblastoma data set, the mean Dice score obtained with the proposed network is 0.7084, Hausdorff Distance-95 is 7.14 and the mean volumetric similarity achieved is 0.8579. With fine-tuning the pre-trained network, the mean dice score improved to 0.7368, Hausdorff Distance-95 decreased to 6.10 and volumetric similarity improved to 0.8736. ASE-Net outperforms the competing networks and can be used for volumetric quantification of post-operative glioblastoma from follow-up MRI scans. The network significantly reduces the probability of over segmentation.
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| 10. |
- Langner, Taro, et al.
(author)
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Identifying morphological indicators of aging with neural networks on large-scale whole-body MRI
- 2020
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In: IEEE Transactions on Medical Imaging. - 0278-0062 .- 1558-254X. ; 39:5, s. 1430-1437
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Journal article (peer-reviewed)abstract
- A wealth of information is contained in images obtained by whole-body magnetic resonance imaging (MRI). Studying the link between the imaged anatomy and properties known from outside sources has the potential to give new insights into the underlying factors that manifest themselves in individual human morphology. In this work we investigate the expression of age-related changes in the whole-body image. A large dataset of about 32,000 subjects scanned from neck to knee and aged 44–82 years from the UK Biobank study was used for a machine-based analysis. We trained a convolutional neural network based on the VGG16 architecture to predict the age of a given subject based on image data from these scans. In 10-fold cross-validation on 23,000 of these images the network reached a mean absolute error (MAE) of 2.49 years (R 2 = 0.83) and showed consistent performance on a separate test set of another 8,000 images. On a second test set of 100 images the network outperformed the averaged estimates given by three experienced radiologists, which reached an MAE of 5.58 years (R 2 = 0.08), by more than three years on average. In an attempt to explain these findings, we employ saliency analysis that opens up the image-based criteria used by the automated method to human interpretation. We aggregate the saliency into a single anatomical visualization which clearly highlights structures in the aortic arch and knee as primary indicators of age.
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