Uniqueness of black holes with bubbles in minimal supergravity

We generalize uniqueness theorems for non-extremal black holes with three mutually independent Killing vector fields in five-dimensional minimal supergravity in order to account for the existence of non-trivial two-cycles in the domain of outer communication. The black hole space-times we consider may contain multiple disconnected horizons and be asymptotically flat or asymptotically Kaluza–Klein. We show that in order to uniquely specify the black hole space-time, besides providing its domain structure and a set of asymptotic and local charges, it is necessary to measure the magnetic fluxes that support the two-cycles as well as fluxes in the two semi-infinite rotation planes of the domain diagram.

The algebraic density property for affine toric varieties

In this paper we generalize the algebraic density property to not necessarily smooth affine varieties relative to some closed subvariety containing the singular locus. This property implies the remarkable approximation results for holomorphic automorphisms of the Andersén–Lempert theory. We show that an affine toric variety X satisfies this algebraic density property relative to a closed T-invariant subvariety Y if and only if X∖Y≠TX∖Y≠T. For toric surfaces we are able to classify those which possess a strong version of the algebraic density property (relative to the singular locus). The main ingredient in this classification is our proof of an equivariant version of Brunella's famous classification of complete algebraic vector fields in the affine plane.

Monte Carlo Dose Calculation on Deforming Anatomy

This article presents the implementation and validation of a dose calculation approach for deforming anatomical objects. Deformation is represented by deformation vector fields leading to deformed voxel grids representing the different deformation scenarios. Particle transport in the resulting deformed voxels is handled through the approximation of voxel surfaces by triangles in the geometry implementation of the Swiss Monte Carlo Plan framework. The focus lies on the validation methodology which uses computational phantoms representing the same physical object through regular and irregular voxel grids. These phantoms are chosen such that the new implementation for a deformed voxel grid can be compared directly with an established dose calculation algorithm for regular grids. Furthermore, separate validation of the aspects voxel geometry and the density changes resulting from deformation is achieved through suitable design of the validation phantom. We show that equivalent results are obtained with the proposed method and that no statistically significant errors are introduced through the implementation for irregular voxel geometries. This enables the use of the presented and validated implementation for further investigations of dose calculation on deforming anatomy.

Constraints on the effective fluid theory of stationary branes

We develop further the effective fluid theory of stationary branes. This formalism applies to stationary blackfolds as well as to other equilibrium brane systems at finite temperature. The effective theory is described by a Lagrangian containing the information about the elastic dynamics of the brane embedding as well as the hydrodynamics of the effective fluid living on the brane. The Lagrangian is corrected order-by-order in a derivative expansion, where we take into account the dipole moment of the brane which encompasses finite-thickness corrections, including transverse spin. We describe how to extract the thermodynamics from the Lagrangian and we obtain constraints on the higher-derivative terms with one and two derivatives. These constraints follow by comparing the brane thermodynamics with the conserved currents associated with background Killing vector fields. In particular, we fix uniquely the one- and two-derivative terms describing the coupling of the transverse spin to the background space-time. Finally, we apply our formalism to two blackfold examples, the black tori and charged black rings and compare the latter to a numerically generated solution.

Increased airway smooth muscle mass in children with asthma, cystic fibrosis, and non-cystic fibrosis bronchiectasis

RATIONALE: Structural alterations to airway smooth muscle (ASM) are a feature of asthma and cystic fibrosis (CF) in adults. OBJECTIVES: We investigated whether increase in ASM mass is already present in children with chronic inflammatory lung disease. METHODS: Fiberoptic bronchoscopy was performed in 78 children (median age [IQR], 11.3 [8.5-13.8] yr): 24 with asthma, 27 with CF, 16 with non-CF bronchiectasis (BX), and 11 control children without lower respiratory tract disease. Endobronchial biopsy ASM content and myocyte number and size were quantified using stereology. MEASUREMENTS AND MAIN RESULTS: The median (IQR) volume fraction of subepithelial tissue occupied by ASM was increased in the children with asthma (0.27 [0.12-0.49]; P < 0.0001), CF (0.12 [0.06-0.21]; P < 0.01), and BX (0.16 [0.04-0.21]; P < 0.01) compared with control subjects (0.04 [0.02-0.05]). ASM content was related to bronchodilator responsiveness in the asthmatic group (r = 0.66, P < 0.01). Median (IQR) myocyte number (cells per mm(2) of reticular basement membrane) was 8,204 (5,270-11,749; P < 0.05) in children with asthma, 4,504 (2,838-8,962; not significant) in children with CF, 4,971 (3,476-10,057; not significant) in children with BX, and 1,944 (1,596-6,318) in control subjects. Mean (SD) myocyte size (mum(3)) was 3,344 (801; P < 0.01) in children with asthma, 3,264 (809; P < 0.01) in children with CF, 3,177 (873; P < 0.05) in children with BX, and 1,927 (386) in control subjects. In all disease groups, the volume fraction of ASM in subepithelial tissue was related to myocyte number (asthma: r = 0.84, P < 0.001; CF: r = 0.81, P < 0.01; BX: r = 0.95, P < 0.001), but not to myocyte size. CONCLUSIONS: Increases in ASM (both number and size) occur in children with chronic inflammatory lung diseases that include CF, asthma, and BX.

The nociceptive withdrawal reflex: Normative values of thresholds and reflex receptive fields

Assessments of spinal nociceptive withdrawal reflexes can be used in human research both to evaluate the effect of analgesics and explore pain mechanisms related to sensitization. Before the reflex can be used as a clinical tool, normative values need to be determined in large scale studies. The aim of this study was to determine the reference values of spinal nociceptive reflexes and subjective pain thresholds (to single and repeated stimulation), and of the area of the reflex receptive fields (RRF) in 300 pain-free volunteers. The influences of gender, age, height, weight, body-mass index (BMI), body side of testing, depression, anxiety, catastrophizing and parameters of Short-Form 36 (SF-36) were analyzed by multiple regressions. The 95% confidence intervals were determined for all the tests as normative values. Age had a statistically and quantitatively significant impact on the subjective pain threshold to single stimuli. The reflex threshold to single stimulus was lower on the dominant compared to the non-dominant side. Depression had a negative impact on the subjective pain threshold to single stimuli. All the other analyses either did not reveal statistical significance or displayed quantitatively insignificant correlations. In conclusion, normative values of parameters related to the spinal nociceptive reflex were determined. This allows their clinical application for assessing central hyperexcitability in individual patients. The parameters investigated explore different aspects of sensitization processes that are largely independent of demographic characteristics, cognitive and affective factors.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Leukaemia, brain tumours and exposure to extremely low frequency magnetic fields: cohort study of Swiss railway employees

AIMS: To investigate the relationship between extremely low frequency magnetic field (ELF-MF) exposure and mortality from leukaemia and brain tumour in a cohort of Swiss railway workers. METHODS: 20,141 Swiss railway employees with 464,129 person-years of follow-up between 1972 and 2002 were studied. Mortality rates for leukaemia and brain tumour of highly exposed train drivers (21 muT average annual exposure) were compared with medium and low exposed occupational groups (i.e. station masters with an average exposure of 1 muT). In addition, individual cumulative exposure was calculated from on-site measurements and modelling of past exposures. RESULTS: The hazard ratio (HR) for leukaemia mortality of train drivers was 1.43 (95% CI 0.74 to 2.77) compared with station masters. For myeloid leukaemia the HR of train drivers was 4.74 (95% CI 1.04 to 21.60) and for Hodgkin's disease 3.29 (95% CI 0.69 to 15.63). Lymphoid leukaemia, non-Hodgkin's disease and brain tumour mortality were not associated with magnetic field exposure. Concordant results were obtained from analyses based on individual cumulative exposure. CONCLUSIONS: Some evidence of an exposure-response association was found for myeloid leukaemia and Hodgkin's disease, but not for other haematopoietic and lymphatic malignancies and brain tumours.

Statistical shape analysis via principal factor analysis

Statistical shape analysis techniques commonly employed in the medical imaging community, such as active shape models or active appearance models, rely on principal component analysis (PCA) to decompose shape variability into a reduced set of interpretable components. In this paper we propose principal factor analysis (PFA) as an alternative and complementary tool to PCA providing a decomposition into modes of variation that can be more easily interpretable, while still being a linear efficient technique that performs dimensionality reduction (as opposed to independent component analysis, ICA). The key difference between PFA and PCA is that PFA models covariance between variables, rather than the total variance in the data. The added value of PFA is illustrated on 2D landmark data of corpora callosa outlines. Then, a study of the 3D shape variability of the human left femur is performed. Finally, we report results on vector-valued 3D deformation fields resulting from non-rigid registration of ventricles in MRI of the brain.