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- Bauters, Marijn, et al.
(författare)
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Contrasting nitrogen fluxes in African tropical forests of the Congo Basin
- 2019
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Ingår i: Ecological Monographs. - : Wiley. - 0012-9615 .- 1557-7015. ; 89:1
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Tidskriftsartikel (refereegranskat)abstract
- The observation of high losses of bioavailable nitrogen (N) and N richness in tropical forests is paradoxical with an apparent lack of N input. Hence, the current concept asserts that biological nitrogen fixation (BNF) must be a major N input for tropical forests. However, well-characterized N cycles are rare and geographically biased; organic N compounds are often neglected and soil gross N cycling is not well quantified. We conducted comprehensive N input and output measurements in four tropical forest types of the Congo Basin with contrasting biotic (mycorrhizal association) and abiotic (lowland–highland) environments. In 12 standardized setups, we monitored N deposition, throughfall, litterfall, leaching, and export during one hydrological year and completed this empirical N budget with nitrous oxide (N2O) flux measurement campaigns in both wet and dry season and insitu gross soil N transformations using 15N-tracing and numerical modeling. We found that all forests showed a very tight soil N cycle, with gross mineralization to immobilization ratios (M/I) close to 1 and relatively low gross nitrification to mineralization ratios (N/M). This was in line with the observation of dissolved organic nitrogen (DON) dominating N losses for the most abundant, arbuscular mycorrhizal associated, lowland forest type, but in contrast with high losses of dissolved inorganic nitrogen (DIN) in all other forest types. Altogether, our observations show that different forest types in central Africa exhibit N fluxes of contrasting magnitudes and N-species composition. In contrast to many Neotropical forests, our estimated N budgets of central African forests are imbalanced by a higher N input than output, with organic N contributing significantly to the input-output balance. This suggests that important other losses that are unaccounted for (e.g., NOx and N2 as well as particulate N) might play a major role in the N cycle of mature African tropical forests.
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| 3. |
- Geroldinger, Martin, et al.
(författare)
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Statistical recommendations for count, binary, and ordinal data in rare disease cross-over trials
- 2023
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Ingår i: Orphanet Journal of Rare Diseases. - : BioMed Central (BMC). - 1750-1172. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundRecommendations for statistical methods in rare disease trials are scarce, especially for cross-over designs. As a result various state-of-the-art methodologies were compared as neutrally as possible using an illustrative data set from epidermolysis bullosa research to build recommendations for count, binary, and ordinal outcome variables. For this purpose, parametric (model averaging), semiparametric (generalized estimating equations type [GEE-like]) and nonparametric (generalized pairwise comparisons [GPC] and a marginal model implemented in the R package nparLD) methods were chosen by an international consortium of statisticians.ResultsIt was found that there is no uniformly best method for the aforementioned types of outcome variables, but in particular situations, there are methods that perform better than others. Especially if maximizing power is the primary goal, the prioritized unmatched GPC method was able to achieve particularly good results, besides being appropriate for prioritizing clinically relevant time points. Model averaging led to favorable results in some scenarios especially within the binary outcome setting and, like the GEE-like semiparametric method, also allows for considering period and carry-over effects properly. Inference based on the nonparametric marginal model was able to achieve high power, especially in the ordinal outcome scenario, despite small sample sizes due to separate testing of treatment periods, and is suitable when longitudinal and interaction effects have to be considered.ConclusionOverall, a balance has to be found between achieving high power, accounting for cross-over, period, or carry-over effects, and prioritizing clinically relevant time points.
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| 4. |
- Nyberg, Joakim, 1978-, et al.
(författare)
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Optimizing designs in clinical trials with an application in treatment of Epidermolysis bullosa simplex, a rare genetic skin disease
- 2024
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Ingår i: Computational Statistics & Data Analysis. - : Elsevier. - 0167-9473 .- 1872-7352. ; 199
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Tidskriftsartikel (refereegranskat)abstract
- Epidermolysis bullosa simplex (EBS) skin disease is a rare disease, which renders the use of optimal design techniques especially important to maximize the potential information in a future study, that is, to make efficient use of the limited number of available subjects and observations. A generalized linear mixed effects model (GLMM), built on an EBS trial was used to optimize the design. The model assumed a full treatment effect in the follow-up period. In addition to this model, two models with either no assumed treatment effect or a linearly declining treatment effect in the follow-up were assumed. The information gain and loss when changing the number of EBS blisters counts, altering the duration of the treatment as well as changing the study period was assessed. In addition, optimization of the EBS blister assessment times was performed. The optimization was utilizing the derived Fisher information matrix for the GLMM with EBS blister counts and the information gain and loss was quantified by D-optimal efficiency. The optimization results indicated that using optimal assessment times increases the information of about 110120%, varying slightly between the assumed treatment models. In addition, the result showed that the assessment times were also sensitive to be moved +/- one week, but assessment times within +/- two days were not decreasing the information as long as three assessments (out of four assessments in the trial period) were within the treatment period and not in the follow-up period. Increasing the number of assessments to six or five per trial period increased the information to 130% and 115%, respectively, while decreasing the number of assessments to two or three, decreased the information to 50% and 80%, respectively. Increasing the length of the trial period had a minor impact on the information, while increasing the treatment period by two and four weeks had a larger impact, 120% and 130%, respectively. To conclude, general applications of optimal design methodology, derivation of the Fisher information matrix for GLMM with count data and examples on how optimal design could be used when designing trials for treatment of the EBS disease is presented. The methodology is also of interest for study designs where maximizing the information is essential. Therefore, a general applied research guidance for using optimal design is also provided.
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| 6. |
- Rubino, Stefano, 1978-, et al.
(författare)
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Simulation of magnetic circular dichroism in the electron microscope
- 2010
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Ingår i: Journal of Physics D. - : IOP Publishing. - 0022-3727 .- 1361-6463. ; 43:47, s. 474005-
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Tidskriftsartikel (refereegranskat)abstract
- As electron energy-loss spectroscopy (EELS) and x-ray absorption spectroscopy (XAS) probe the same transitions from core–shell states to unoccupied states above the Fermi energy, it should always be possible to apply the two techniques to the same physical phenomena, such as magnetic dichroism, and obtain the same information. Indeed, the similarity in the expression of the electron and x-ray cross-sections had been already exploited to prove the equivalence of x-ray magnetic linear dichroism and anisotropy in EELS, by noting that the polarization vector of a photon plays the same role as the momentum transfer in electron scattering. Recently, the same was proven true for x-ray magnetic circular dichroism (XMCD) by establishing a new TEM technique called EMCD (electron energy-loss magnetic chiral dichroism) (Schattschneider P et al 2006 Nature 441 486–8), which makes use of special electron scattering conditions to force the absorption of a circularly polarized virtual photon.The intrinsic advantage of EMCD over XMCD is the high spatial resolution of electron microscopes, which are readily available. Among the particular obstacles in EMCD that do not exist for synchrotron radiation, is the notoriously low signal and the very particular scattering conditions necessary to observe a chiral dichroic signal. In spite of that, impressive progress has been made in recent years. The signal strength could be considerably increased, and some innovations such as using a convergent beam have been introduced. EMCD has evolved into several techniques, which make full use of the versatility of the TEM and energy filtering, spectroscopy or STEM conditions (Rubino S 2007 Magnetic circular dichroism in the transmission electron microscope PhD Thesis Vienna University of Technology, Vienna, Austria).
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| 7. |
- Spiegelberg, Jakob
(författare)
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Signal Processing Tools for Electron Microscopy
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The detection of weak signals in noisy data is a problem which occurs across various disciplines. Here, the signal of interest is the spectral signature of the electron magnetic chiral dichroism (EMCD) effect. In principle, EMCD allows for the measurement of local magnetic structures in the electron microscope, its spatial resolution, versatility and low hardware requirements giving it an eminent position among competing measurement techniques. However, experimental shortcomings as well as intrinsically low signal to noise ratio render its measurement challenging to the present day. This thesis explores how posterior data processing may aid the analysis of various data from the electron microscope. Following a brief introduction to different signals arising in the microscope and a yet briefer survey of the state of the art of EMCD measurements, noise removal strategies are presented. Afterwards, gears are shifted to discuss the separation of mixed signals into their physically meaningful source components based on their assumed mathematical characteristics, so called blind source separation (BSS). A data processing workflow for detecting weak signals in noisy spectra is derived from these considerations, ultimately culminating in several demonstrations of the extraction of EMCD signals. While the focus of the thesis does lie on data processing strategies for EMCD detection, the approaches presented here are similarly applicable in other situations. Related topics such as the general analysis of hyperspectral images using BSS methods or the fast analysis of large data sets are also discussed.
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| 8. |
- Verbeeck, Johan, et al.
(författare)
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How to Analyze Continuous and Discrete Repeated Measures in Small-Sample Cross-Over Trials?
- 2023
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Ingår i: Biometrics. - : Oxford University Press. - 0006-341X .- 1541-0420. ; 79:4, s. 3998-4011
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Tidskriftsartikel (refereegranskat)abstract
- To optimize the use of data from a small number of subjects in rare disease trials, an at first sight advantageous design is the repeated measures cross-over design. However, it is unclear how these within-treatment period and within-subject clustered data are best analyzed in small-sample trials. In a real-data simulation study based upon a recent epidermolysis bullosa simplex trial using this design, we compare non-parametric marginal models, generalized pairwise comparison models, GEE-type models and parametric model averaging for both repeated binary and count data. The recommendation of which methodology to use in rare disease trials with a repeated measures cross-over design depends on the type of outcome and the number of time points the treatment has an effect on. The non-parametric marginal model testing the treatment-time-interaction effect is suitable for detecting between group differences in the shapes of the longitudinal profiles. For binary outcomes with the treatment effect on a single time point, the parametric model averaging method is recommended, while in the other cases the unmatched generalized pairwise comparison methodology is recommended. Both provide an easily interpretable effect size measure, and do not require exclusion of periods or subjects due to incompleteness.
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