Linear Shape Deformation Models with Local Support Using Graph-based Structured Matrix Factorisation

Representing 3D shape deformations by linear models in high-dimensional space has many applications in computer vision and medical imaging, such as shape-based interpolation or segmentation. Commonly, using Principal Components Analysis a low-dimensional (affine) subspace of the high-dimensional shape space is determined. However, the resulting factors (the most dominant eigenvectors of the covariance matrix) have global support, i.e. changing the coefficient of a single factor deforms the entire shape. In this paper, a method to obtain deformation factors with local support is presented. The benefits of such models include better flexibility and interpretability as well as the possibility of interactively deforming shapes locally. For that, based on a well-grounded theoretical motivation, we formulate a matrix factorisation problem employing sparsity and graph-based regularisation terms. We demonstrate that for brain shapes our method outperforms the state of the art in local support models with respect to generalisation ability and sparse shape reconstruction, whereas for human body shapes our method gives more realistic deformations.Comment: Please cite CVPR 2016 versio

A Solution for Multi-Alignment by Transformation Synchronisation

The alignment of a set of objects by means of transformations plays an important role in computer vision. Whilst the case for only two objects can be solved globally, when multiple objects are considered usually iterative methods are used. In practice the iterative methods perform well if the relative transformations between any pair of objects are free of noise. However, if only noisy relative transformations are available (e.g. due to missing data or wrong correspondences) the iterative methods may fail. Based on the observation that the underlying noise-free transformations can be retrieved from the null space of a matrix that can directly be obtained from pairwise alignments, this paper presents a novel method for the synchronisation of pairwise transformations such that they are transitively consistent. Simulations demonstrate that for noisy transformations, a large proportion of missing data and even for wrong correspondence assignments the method delivers encouraging results.Comment: Accepted for CVPR 2015 (please cite CVPR version

Electronic structure and dynamics of optically excited single-wall carbon nanotubes

We have studied the electronic structure and charge-carrier dynamics of individual single-wall carbon nanotubes (SWNTs) and nanotube ropes using optical and electron-spectroscopic techniques. The electronic structure of semiconducting SWNTs in the band-gap region is analyzed using near-infrared absorption spectroscopy. A semi-empirical expression for $E_{11}^{\rm S}$ transition energies, based on tight-binding calculations is found to give striking agreement with experimental data. Time-resolved PL from dispersed SWNT-micelles shows a decay with a time constant of about 15 ps. Using time-resolved photoemission we also find that the electron-phonon ({\it e-ph}) coupling in metallic tubes is characterized by a very small {\it e-ph} mass-enhancement of 0.0004. Ultrafast electron-electron scattering of photo-excited carriers in nanotube ropes is finally found to lead to internal thermalization of the electronic system within about 200 fs.Comment: 10 pages, 10 figures, submitted to Applied Physics

Social environment shapes female settlement decisions in a solitary carnivore

How and where a female selects an area to settle and breed is of central importance in dispersal and population ecology as it governs range expansion and gene flow. Social structure and organization have been shown to influence settlement decisions, but its importance in the settlement of large, solitary mammals is largely unknown. We investigate how the identity of overlapping conspecifics on the landscape, acquired during the maternal care period, influences the selection of settlement home ranges in a non-territorial, solitary mammal using location data of 56 female brown bears (Ursus arctos). We used a resource selection function to determine whether females' settlement behavior was influenced by the presence of their mother, related females, familiar females, and female population density. Hunting may remove mothers and result in socio-spatial changes before settlement. We compared overlap between settling females and their mother's concurrent or most recent home ranges to examine the settling female's response to the absence or presence of her mother on the landscape. We found that females selected settlement home ranges that overlapped their mother's home range, familiar females, that is, those they had previously overlapped with, and areas with higher density than their natal ranges. However, they did not select areas overlapping related females. We also found that when mothers were removed from the landscape, female offspring selected settlement home ranges with greater overlap of their mother's range, compared with mothers who were alive. Our results suggest that females are acquiring and using information about their social environment when making settlement decisions.Information about the social environment may help female brown bears to select a settlement home range for breeding. We found that a female uses the identity of other females that overlapped her natal home range and female density when making settlement decisions. Specifically, females select settlement home ranges that overlap with home ranges of their mothers and familiar females known from their natal period. Relatedness does not appear to influence settlement decisions in this population

The Effect of Structural Distortions on the Electronic Structure of Carbon Nanotubes

We calculated the effects of structural distortions on the electronic structure of carbon nanotubes. The key modification of the electronic structure brought about by bending a nanotube involves an increased mixing of $\sigma$ and $\pi$-states. This mixing leads to an enhanced density-of-states in the valence band near the Fermi energy region. While in a straight tube the states accessible for electrical conduction are essentially pure C($2p_{\pi}$)-states, they acquire significant C($2sp_{\sigma}$) character upon bending. Bending also leads to a charge polarization of the C-C bonds in the deformed region reminiscent of interface dipole formation. Scattering of conduction electrons at the distorted regions may lead to electron localization at low temperatures.Comment: 11 pages and 4 figures, (figure 4 corrected

The role of familial conflict in home range settlement and fitness of a solitary mammal

Familial conflict, including parent–offspring conflict (POC) and sibling competition (SC), occurs when an individual maximizes its access to a limiting resource at the expense of a related individual. The role of familial conflict for competition over space as a limited resource remains relatively unexplored. In this study, we examined how familial conflict affects natal dispersal and settlement decisions of a solitary mammal, the brown bear, Ursus arctos, and tested whether these settlement patterns covary with fitness. First, we tested whether the distance settled from the natal range was affected by aspects of POC (litter type: single versus multiple; mother's age; mother's living status) and SC (settled near versus far from the natal home range, body size). We then modelled how distance settled from the natal range influenced three measures of fitness: survival to reproduction, lifetime reproductive success and lifetime survival. In line with POC, we found that daughters settled twice as far from the natal range when their mother was alive than when she was dead. We found strong evidence for SC where in sibling pairs, the ‘near’ sister settled nearly three times closer to the natal range than her sibling. We found contradictory patterns in fitness outcomes based on settlement distance, such that females settling closer to the natal range had higher lifetime survival but were less likely to successfully wean at least one offspring. Despite survival advantages gained by settling closer to the natal range, there was no evidence that settlement distance influenced lifetime reproductive success. Fitness outcomes in this population may be influenced more by factors related to annual hunting than by familial conflict or proximity to the natal range

The role of familial conflict in home range settlement and fitness of a solitary mammal

Journal of evolutionary biology Blackwell/wileyFamilial conflict, including parenteoffspring conflict (POC) and sibling competition (SC), occurs when an individual maximizes its access to a limiting resource at the expense of a related individual. The role of familial conflict for competition over space as a limited resource remains relatively unexplored. In this study, we examined how familial conflict affects natal dispersal and settlement decisions of a solitary mammal, the brown bear, Ursus arctos, and tested whether these settlement patterns covary with fitness. First, we tested whether the distance settled from the natal range was affected by aspects of POC (litter type: single versus multiple; mother's age; mother's living status) and SC (settled near versus far from the natal home range, body size). We then modelled how distance settled from the natal range influenced three measures of fitness: survival to reproduction, lifetime reproductive success and lifetime survival. In line with POC, we found that daughters settled twice as far from the natal range when their mother was alive than when she was dead. We found strong evidence for SC where in sibling pairs, the ‘near’ sister settled nearly three times closer to the natal range than her sibling. We found contradictory patterns in fitness outcomes based on settlement distance, such that females settling closer to the natal range had higher lifetime survival but were less likely to successfully wean at least one offspring. Despite survival advantages gained by settling closer to the natal range, there was no evidence that settlement distance influenced lifetime reproductive success. Fitness outcomes in this population may be influenced more by factors related to annual hunting than by familial conflict or proximity to the natal range. dispersal fitness parenteoffspring conflict reproductive success sibling competitionpublishedVersio

Effect of an Herbal/Botanical Supplement on Strength, Balance, and Muscle Function Following 12-Weeks of Resistance Training: A Placebo Controlled Study

Background: StemSport (SS; StemTech International, Inc. San Clemente, CA) contains a proprietary blend of the botanical Aphanizomenon flos-aquae and several herbal antioxidant and anti-inflammatory substances. SS has been purported to accelerate tissue repair and restore muscle function following resistance exercise. Here, we examine the effects of SS supplementation on strength adaptations resulting from a 12-week resistance training program in healthy young adults. Methods: Twenty-four young adults (16 males, 8 females, mean age = 20.5 ± 1.9 years, mass = 70.9 ± 11.9 kg, stature = 176.6 ± 9.9 cm) completed the twelve week training program. The study design was a double-blind, placebo controlled parallel group trial. Subjects either received placebo or StemSport supplement (SS; mg/day) during the training. 1-RM bench press, 1-RM leg press, vertical jump height, balance (star excursion and center of mass excursion), isokinetic strength (elbow and knee flexion/extension) and perception of recovery were measured at baseline and following the 12-week training intervention. Results: Resistance training increased 1-RM strength (p \u3c 0.008), vertical jump height (p \u3c 0.03), and isokinetic strength (p \u3c 0.05) in both SS and placebo groups. No significant group-by-time interactions were observed (all p-values \u3e0.10). Conclusions: These data suggest that compared to placebo, the SS herbal/botanical supplement did not enhance training induced adaptations to strength, balance, and muscle function above strength training alone

Visualization of the medial forebrain bundle using diffusion tensor imaging

Diffusion tensor imaging is a technique that enables physicians the portrayal of white matter tracts in vivo. We used this technique in order to depict the medial forebrain bundle (MFB) in 15 consecutive patients between 2012 and 2015. Men and women of all ages were included. There were six women and nine men. The mean age was 58.6 years (39–77). Nine patients were candidates for an eventual deep brain stimulation. Eight of them suffered from Parkinson‘s disease and one had multiple sclerosis. The remaining six patients suffered from different lesions which were situated in the frontal lobe. These were 2 metastasis, 2 meningiomas, 1 cerebral bleeding, and 1 glioblastoma. We used a 3DT1-sequence for the navigation. Furthermore T2- and DTI- sequences were performed. The FOV was 200 × 200 mm2, slice thickness 2 mm, and an acquisition matrix of 96 × 96 yielding nearly isotropic voxels of 2 × 2 × 2 mm. 3-Tesla-MRI was carried out strictly axial using 32 gradient directions and one b0-image. We used Echo-Planar-Imaging (EPI) and ASSET parallel imaging with an acceleration factor of 2. b-value was 800 s/mm2. The maximal angle was 50°. Additional scanning time was < 9 min. We were able to visualize the MFB in 12 of our patients bilaterally and in the remaining three patients we depicted the MFB on one side. It was the contralateral side of the lesion. These were 2 meningiomas and one metastasis. Portrayal of the MFB is possible for everyday routine for neurosurgical interventions. As part of the reward circuitry it might be of substantial importance for neurosurgeons during deep brain stimulation in patients with psychiatric disorders. Surgery in this part of the brain should always take the preservation of this white matter tract into account

Machine learning models for diagnosis and prognosis of Parkinson's disease using brain imaging: general overview, main challenges, and future directions

Parkinson’s disease (PD) is a progressive and complex neurodegenerative disorder associated with age that affects motor and cognitive functions. As there is currently no cure, early diagnosis and accurate prognosis are essential to increase the effectiveness of treatment and control its symptoms. Medical imaging, specifically magnetic resonance imaging (MRI), has emerged as a valuable tool for developing support systems to assist in diagnosis and prognosis. The current literature aims to improve understanding of the disease’s structural and functional manifestations in the brain. By applying artificial intelligence to neuroimaging, such as deep learning (DL) and other machine learning (ML) techniques, previously unknown relationships and patterns can be revealed in this high-dimensional data. However, several issues must be addressed before these solutions can be safely integrated into clinical practice. This review provides a comprehensive overview of recent ML techniques analyzed for the automatic diagnosis and prognosis of PD in brain MRI. The main challenges in applying ML to medical diagnosis and its implications for PD are also addressed, including current limitations for safe translation into hospitals. These challenges are analyzed at three levels: disease-specific, task- specific, and technology-specific. Finally, potential future directions for each challenge and future perspectives are discusse