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- Chumak, A. V., et al.
(författare)
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Advances in Magnetics Roadmap on Spin-Wave Computing
- 2022
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Ingår i: IEEE Transactions on Magnetics. - 0018-9464. ; 58:6
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Tidskriftsartikel (refereegranskat)abstract
- Magnonics addresses the physical properties of spin waves and utilizes them for data processing. Scalability down to atomic dimensions, operation in the GHz-to-THz frequency range, utilization of nonlinear and nonreciprocal phenomena, and compatibility with CMOS are just a few of many advantages offered by magnons. Although magnonics is still primarily positioned in the academic domain, the scientific and technological challenges of the field are being extensively investigated, and many proof-of-concept prototypes have already been realized in laboratories. This roadmap is a product of the collective work of many authors that covers versatile spin-wave computing approaches, conceptual building blocks, and underlying physical phenomena. In particular, the roadmap discusses the computation operations with Boolean digital data, unconventional approaches like neuromorphic computing, and the progress towards magnon-based quantum computing. The article is organized as a collection of sub-sections grouped into seven large thematic sections. Each sub-section is prepared by one or a group of authors and concludes with a brief description of current challenges and the outlook of further development for each research direction. Author
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| 2. |
- Randler, C., et al.
(författare)
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Animal welfare attitudes : Effects of gender and diet in university samples from 22 countries
- 2021
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Ingår i: Animals. - : MDPI AG. - 2076-2615. ; 11:7
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Tidskriftsartikel (refereegranskat)abstract
- Animal Welfare Attitudes (AWA) are defined as human attitudes towards the welfare of animals in different dimensions and settings. Demographic factors, such as age and gender are associated with AWA. The aim of this study was to assess gender differences among university students in a large convenience sample from twenty-two nations in AWA. A total of 7914 people participated in the study (5155 women, 2711 men, 48 diverse). Participants completed a questionnaire that collected demographic data, typical diet and responses to the Composite Respect for Animals Scale Short version (CRAS-S). In addition, we used a measure of gender empowerment from the Human Development Report. The largest variance in AWA was explained by diet, followed by country and gender. In terms of diet, 6385 participants reported to be omnivores, 296 as pescatarian, 637 ate a vegetarian diet and 434 were vegans (n = 162 without answer). Diet was related with CRAS-S scores; people with a vegan diet scored higher in AWA than omnivores. Women scored significantly higher on AWA than men. Furthermore, gender differences in AWA increased as gender inequality decreased. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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| 3. |
- De Jong, VMT, et al.
(författare)
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Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis
- 2022
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Ingår i: BMJ (Clinical research ed.). - : BMJ. - 1756-1833. ; 378, s. e069881-
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveTo externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19.DesignTwo stage individual participant data meta-analysis.SettingSecondary and tertiary care.Participants46 914 patients across 18 countries, admitted to a hospital with polymerase chain reaction confirmed covid-19 from November 2019 to April 2021.Data sourcesMultiple (clustered) cohorts in Brazil, Belgium, China, Czech Republic, Egypt, France, Iran, Israel, Italy, Mexico, Netherlands, Portugal, Russia, Saudi Arabia, Spain, Sweden, United Kingdom, and United States previously identified by a living systematic review of covid-19 prediction models published inThe BMJ, and through PROSPERO, reference checking, and expert knowledge.Model selection and eligibility criteriaPrognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor.MethodsEight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters.Main outcome measures30 day mortality or in-hospital mortality.ResultsDatasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al’s model (0.96, 0.59 to 1.55, 0.21 to 4.28).ConclusionThe prognostic value of the included models varied greatly between the data sources. Although the Knight 4C Mortality Score and Wang clinical model appeared most promising, recalibration (intercept and slope updates) is needed before implementation in routine care.
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| 4. |
- Slator, Paddy J., et al.
(författare)
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Combined diffusion-relaxometry microstructure imaging : Current status and future prospects
- 2021
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 86:6, s. 2987-3011
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Forskningsöversikt (refereegranskat)abstract
- Microstructure imaging seeks to noninvasively measure and map microscopic tissue features by pairing mathematical modeling with tailored MRI protocols. This article reviews an emerging paradigm that has the potential to provide a more detailed assessment of tissue microstructure—combined diffusion-relaxometry imaging. Combined diffusion-relaxometry acquisitions vary multiple MR contrast encodings—such as b-value, gradient direction, inversion time, and echo time—in a multidimensional acquisition space. When paired with suitable analysis techniques, this enables quantification of correlations and coupling between multiple MR parameters—such as diffusivity, (Formula presented.), (Formula presented.), and (Formula presented.). This opens the possibility of disentangling multiple tissue compartments (within voxels) that are indistinguishable with single-contrast scans, enabling a new generation of microstructural maps with improved biological sensitivity and specificity.
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