| 1. |
- Abbas, Sascha, et al.
(författare)
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Dietary intake of vitamin D and calcium and breast cancer risk in the European prospective investigation into cancer and nutrition
- 2013
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Ingår i: Nutrition and Cancer. - : Taylor & Francis. - 0163-5581 .- 1532-7914. ; 65:2, s. 178-187
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Tidskriftsartikel (refereegranskat)abstract
- Studies assessing the effects of vitamin D or calcium intake on breast cancer risk have been inconclusive. Furthermore, few studies have evaluated them jointly. This study is the largest so far examining the association of dietary vitamin D and calcium intake with breast cancer risk in the European Prospective Investigation into Cancer and Nutrition. During a mean follow-up of 8.8 yr, 7760 incident invasive breast cancer cases were identified among 319,985 women. Multivariable Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for pre- and postmenopausal breast cancer risk. Comparing the highest with the lowest quintile of vitamin D intake, HR and 95% CI were 1.07 (0.87-1.32) and 1.02 (0.90-1.16) for pre- and postmenopausal women, respectively. The corresponding HR and 95% CIs for calcium intake were 0.98 (0.80-1.19) and 0.90 (0.79-1.02), respectively. For calcium intake in postmenopausal women, the test for trend was borderline statistically significant (P(trend) = 0.05). There was no significant interaction between vitamin D and calcium intake and cancer risk (P(interaction) = 0.57 and 0.22 in pre- and postmenopausal women, respectively). In this large prospective cohort, we found no evidence for an association between dietary vitamin D or calcium intake and breast cancer risk.
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| 2. |
- Barack, Leor, et al.
(författare)
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Black holes, gravitational waves and fundamental physics : a roadmap
- 2019
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Ingår i: Classical and quantum gravity. - : IOP Publishing. - 0264-9381 .- 1361-6382. ; 36:14
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Forskningsöversikt (refereegranskat)abstract
- The grand challenges of contemporary fundamental physics dark matter, dark energy, vacuum energy, inflation and early universe cosmology, singularities and the hierarchy problem all involve gravity as a key component. And of all gravitational phenomena, black holes stand out in their elegant simplicity, while harbouring some of the most remarkable predictions of General Relativity: event horizons, singularities and ergoregions. The hitherto invisible landscape of the gravitational Universe is being unveiled before our eyes: the historical direct detection of gravitational waves by the LIGO-Virgo collaboration marks the dawn of a new era of scientific exploration. Gravitational-wave astronomy will allow us to test models of black hole formation, growth and evolution, as well as models of gravitational-wave generation and propagation. It will provide evidence for event horizons and ergoregions, test the theory of General Relativity itself, and may reveal the existence of new fundamental fields. The synthesis of these results has the potential to radically reshape our understanding of the cosmos and of the laws of Nature. The purpose of this work is to present a concise, yet comprehensive overview of the state of the art in the relevant fields of research, summarize important open problems, and lay out a roadmap for future progress. This write-up is an initiative taken within the framework of the European Action on 'Black holes, Gravitational waves and Fundamental Physics'.
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| 3. |
- Yoon, Chun Hong, et al.
(författare)
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Unsupervised classification of single-particle X-ray diffraction snapshots by spectral clustering
- 2011
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Ingår i: Optics Express. - 1094-4087. ; 19:17, s. 16542-16549
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Tidskriftsartikel (refereegranskat)abstract
- Single-particle experiments using X-ray Free Electron Lasers produce more than 10(5) snapshots per hour, consisting of an admixture of blank shots (no particle intercepted), and exposures of one or more particles. Experimental data sets also often contain unintentional contamination with different species. We present an unsupervised method able to sort experimental snapshots without recourse to templates, specific noise models, or user-directed learning. The results show 90% agreement with manual classification.
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