Performance and stall limits of a YTF30-P-1 turbofan engine with uniform inlet flow

Performance and stall limits of YTF30-P-1 turbofan engine with uniform compressor inlet flo

Forest Cover Changes in Tropical South and Central America from 1990 to 2005 and Related Carbon Emissions and Removals.

This paper outlines the methods and results for monitoring forest change and resulting carbon emissions for the 1990-2000 and 200-2005 periods carried out over tropical Central and South America. To produce our forest change estimates we used a systematic sample of medium resolution satellite data processed to forest change maps covering 1230 sites of 20 km by 20 km, each located at the degree confluence. Biomass data were spatially associated to each individual sample site so that annual carbon emissions could be estimated. For our study area we estimate that forest cover in the study area had fallen from 763 Mha (s.e. 10 Mha) in 1990 to 715 Mha (s.e. 10 Mha) in 2005. During the same period other wooded land (i.e., non-forest woody vegetation) had fallen from 191 Mha (s.e. 5.5 Mha) to 184 Mha (s.e. 5.5 Mha). This equates to an annual gross loss of 3.74 Mha·y−1 of forests (0.50% annually) between 1990 and 2000, rising to 4.40 Mha·y−1 in the early 2000s (0.61% annually), with Brazil accounting for 69% of the total losses. The annual carbon emissions from the combined loss of forests and other wooded land were calculated to be 482 MtC·y−1 (s.e. 29 MtC·y−1) for the 1990s, and 583 MtC·y−1 (s.e. 48 MtC·y−1) for the 2000 to 2005 period. Our maximum estimate of sinks from forest regrowth in tropical South America is 92 MtC·y−1. These estimates of gross emissions correspond well with the national estimates reported by Brazil, however, they are less than half of those reported in a recent study based on the FAO country statistics, highlighting the need for continued research in this area

Velocity and density profiles of granular flow in channels using lattice gas automaton

We have performed two-dimensional lattice-gas-automaton simulations of granular flow between two parallel planes. We find that the velocity profiles have non-parabolic distributions while simultaneously the density profiles are non-uniform. Under non-slip boundary conditions, deviation of velocity profiles from the parabolic form of newtonian fluids is found to be characterized solely by ratio of maximal velocity at the center to the average velocity, though the ratio depends on the model parameters in a complex manner. We also find that the maximal velocity ($u_{max}$) at the center is a linear function of the driving force (g) as $u_{max} = \alpha g - \delta$ with non-zero $\delta$ in contrast with newtonian fluids. Regarding density profiles, we observe that densities near the boundaries are higher than those in the center. The width of higher densities (above the average density) relative to the channel width is a decreasing function of a variable which scales with the driving force (g), energy dissipation parameter ($\epsilon$) and the width of the system (L) as $g^{\mu} L^{\nu}/\epsilon$ with exponents $\mu = 1.4 \pm 0.1$ and $\nu = 0.5 \pm 0.1$. A phenomenological theory based on a scaling argument is presented to interpret these findings.Comment: Latex, 15 figures, to appear in PR

Tumor tissue-specific biomarkers of colorectal cancer by anatomic location and stage

The progress in the discovery and validation of metabolite biomarkers for the detection of colorectal cancer (CRC) has been hampered by the lack of reproducibility between study cohorts. The majority of discovery-phase biomarker studies have used patient blood samples to identify disease-related metabolites, but this pre-validation phase is confounded by non-specific disease influences on the metabolome. We therefore propose that metabolite biomarker discovery would have greater success and higher reproducibility for CRC if the discovery phase was conducted in tumor tissues, to find metabolites that have higher specificity to the metabolic consequences of the disease, that are then validated in blood samples. This would thereby eliminate any non-tumor and/or body response effects to the disease. In this study, we performed comprehensive untargeted metabolomics analyses on normal (adjacent) colon and tumor tissues from CRC patients, revealing tumor tissue-specific biomarkers (n = 39/group). We identified 28 highly discriminatory tumor tissue metabolite biomarkers of CRC by orthogonal partial least-squares discriminant analysis (OPLS-DA) and univariate analyses (VIP > 1.5, p 0.96, using various models. We further identified five biomarkers that were specific to the anatomic location of tumors in the colon (n = 236). The combination of these five metabolites (S-adenosyl-L-homocysteine, formylmethionine, fucose 1-phosphate, lactate, and phenylalanine) demonstrated high differentiative capability for left- and right-sided colon cancers at stage I by internal cross-validation (AUC = 0.804, 95% confidence interval, CI 0.670–0.940). This study thus revealed nine discriminatory biomarkers of CRC that are now poised for external validation in a future independent cohort of samples. We also discovered a discrete metabolic signature to determine the anatomic location of the tumor at the earliest stage, thus potentially providing clinicians a means to identify individuals that could be triaged for additional screening regimens

Ribosomal oxygenases are structurally conserved from prokaryotes to humans

2-Oxoglutarate (2OG)-dependent oxygenases have important roles in the regulation of gene expression via demethylation of N-methylated chromatin components1,2 and in the hydroxylation of transcription factors3 and splicing factor proteins4. Recently, 2OG-dependent oxygenases that catalyse hydroxylation of transfer RNA5,6,7 and ribosomal proteins8 have been shown to be important in translation relating to cellular growth, TH17-cell differentiation and translational accuracy9,10,11,12. The finding that ribosomal oxygenases (ROXs) occur in organisms ranging from prokaryotes to humans8 raises questions as to their structural and evolutionary relationships. In Escherichia coli, YcfD catalyses arginine hydroxylation in the ribosomal protein L16; in humans, MYC-induced nuclear antigen (MINA53; also known as MINA) and nucleolar protein 66 (NO66) catalyse histidine hydroxylation in the ribosomal proteins RPL27A and RPL8, respectively. The functional assignments of ROXs open therapeutic possibilities via either ROX inhibition or targeting of differentially modified ribosomes. Despite differences in the residue and protein selectivities of prokaryotic and eukaryotic ROXs, comparison of the crystal structures of E. coli YcfD and Rhodothermus marinus YcfD with those of human MINA53 and NO66 reveals highly conserved folds and novel dimerization modes defining a new structural subfamily of 2OG-dependent oxygenases. ROX structures with and without their substrates support their functional assignments as hydroxylases but not demethylases, and reveal how the subfamily has evolved to catalyse the hydroxylation of different residue side chains of ribosomal proteins. Comparison of ROX crystal structures with those of other JmjC-domain-containing hydroxylases, including the hypoxia-inducible factor asparaginyl hydroxylase FIH and histone Nε-methyl lysine demethylases, identifies branch points in 2OG-dependent oxygenase evolution and distinguishes between JmjC-containing hydroxylases and demethylases catalysing modifications of translational and transcriptional machinery. The structures reveal that new protein hydroxylation activities can evolve by changing the coordination position from which the iron-bound substrate-oxidizing species reacts. This coordination flexibility has probably contributed to the evolution of the wide range of reactions catalysed by oxygenases

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Volumetry of [11C]-methionine PET uptake and MRI contrast enhancement in patients with recurrent glioblastoma multiforme

We investigated the relationship between three-dimensional volumetric data of the metabolically active tumour volume assessed using [(11)C]-methionine positron emission tomography (MET-PET) and the area of gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA) enhancement assessed using magnetic resonance imaging (MRI) in patients with recurrent glioblastoma (GBM).MET-PET and contrast-enhanced MRI with Gd-DTPA were performed in 12 uniformly pretreated patients with recurrent GBM. To calculate the volumes in cubic centimetres, a threshold-based volume-of-interest (VOI) analysis of the metabolically active tumour volume (MET uptake indexes of > or = 1.3 and > or = 1.5) and of the area of Gd-DTPA enhancement was performed after coregistration of all images.In all patients, the metabolically active tumour volume as shown using a MET uptake index of > or = 1.3 was larger than the volume of Gd-DTPA enhancement (30.2 + or - 22.4 vs. 13.7 + or - 10.6 cm(3); p = 0.04). Metabolically active tumour volumes as shown using MET uptake indexes of > or =1.3 and > or = 1.5 and the volumes of Gd-DTPA enhancement showed a positive correlation (r = 0.76, p = 0.003, for an index of > or =1.3, and r = 0.74, p = 0.005, for an index of > or =1.5).The present data suggest that in patients with recurrent GBM the metabolically active tumour volume may be substantially underestimated by Gd-DTPA enhancement. The findings support the notion that complementary information derived from MET uptake and Gd-DTPA enhancement may be helpful in developing individualized, patient-tailored therapy strategies in patients with recurrent GBM

The structural plasticity of white matter networks following anterior temporal lobe resection

Anterior temporal lobe resection is an effective treatment for refractory temporal lobe epilepsy. The structural consequences of such surgery in the white matter, and how these relate to language function after surgery remain unknown. We carried out a longitudinal study with diffusion tensor imaging in 26 left and 20 right temporal lobe epilepsy patients before and a mean of 4.5 months after anterior temporal lobe resection. The whole-brain analysis technique tract-based spatial statistics was used to compare pre- and postoperative data in the left and right temporal lobe epilepsy groups separately. We observed widespread, significant, mean 7%, decreases in fractional anisotropy in white matter networks connected to the area of resection, following both left and right temporal lobe resections. However, we also observed a widespread, mean 8%, increase in fractional anisotropy after left anterior temporal lobe resection in the ipsilateral external capsule and posterior limb of the internal capsule, and corona radiata. These findings were confirmed on analysis of the native clusters and hand drawn regions of interest. Postoperative tractography seeded from this area suggests that this cluster is part of the ventro-medial language network. The mean pre- and postoperative fractional anisotropy and parallel diffusivity in this cluster were significantly correlated with postoperative verbal fluency and naming test scores. In addition, the percentage change in parallel diffusivity in this cluster was correlated with the percentage change in verbal fluency after anterior temporal lobe resection, such that the bigger the increase in parallel diffusivity, the smaller the fall in language proficiency after surgery. We suggest that the findings of increased fractional anisotropy in this ventro-medial language network represent structural reorganization in response to the anterior temporal lobe resection, which may damage the more susceptible dorso-lateral language pathway. These findings have important implications for our understanding of brain injury and rehabilitation, and may also prove useful in the prediction and minimization of postoperative language deficits

Achtsamkeit in systemischer Beratung und Coaching

Als mich Markus Hänsel fragte, ob ich einen Beitrag in dem Band >>Die spirituelle Dimension in Coaching und Beratung<< schreiben würde, sagte ich freudig zu. Um zu beantworten, was das ist, diese >>spirituelle Dimension<<, muss man vielleicht zunächst einmal klären, was die >>nichtspirituelle Dimension<< ist. Dazu fällt mir eine Geschichte ein:Fragt ein Klient in dieser Sache seinen Berater: >>Was ist der Unterschied zwischen der spirituellen Dimension und der nichtspirituellen Dimension?<< Entgegnet der Berater: >>Die nichtspirituelle Dimension glaubt, es gäbe einen.<< Jeder Artikel über Spiritualität in Beratung und Coaching müsste eigentlich hier enden, da mit dieser kurzen Antwort alles über das Thema gesagt ist. Der Rest ist die Erfahrung. Die Entfaltung der Ereignisse im Beratungsprozess. Die Erfahrung von Gelingen oder Misslingen, Inspiration, Verbundenheit und Trennung. Der Begriff spirituelle Erfahrung ist eine Eingrenzung der Erfahrungsebene, die eine Trennlinie markiert und gewisse Erfahrungen als nichtspirituelle denunziert. Damit unterliegen wir schon der ersten Täuschung, um die es unter anderem in diesem Beitrag gehen soll. Der Zen-Patriarch Dajian Huineng (638-713) hat an dieser Stelle gesagt, der reine Geist finde sich in unserem unreinen Geist. Beides ist eins. Die Unterscheidung treffen wir (vgl. McRae, 2000)