A quasi-Monte Carlo method for computing areas of point-sampled surfaces

A novel and efficient quasi-Monte Carlo method for computing the area of a point-sampled surface with associated surface normal for each point is presented. Our method operates directly on the point cloud without any surface reconstruction procedure. Using the Cauchy–Crofton formula, the area of the point-sampled surface is calculated by counting the number of intersection points between the point cloud and a set of uniformly distributed lines generated with low-discrepancy sequences. Based on a clustering technique, we also propose an effective algorithm for computing the intersection points of a line with the point-sampled surface. By testing on a number of point-based models, experiments suggest that our method is more robust and more efficient than those conventional approaches based on surface reconstruction.postprin

Efficient and robust reconstruction of botanical branching structure from laser scanned points

This paper presents a reconstruction pipeline for recovering branching structure of trees from laser scanned data points. The process is made up of two main blocks: segmentation and reconstruction. Based on a variational k-means clustering algorithm, cylindrical components and ramified regions of data points are identified and located. An adjacency graph is then built from neighborhood information of components. Simple heuristics allow us to extract a skeleton structure and identify branches from the graph. Finally, a B-spline model is computed to give a compact and accurate reconstruction of the branching system. © 2009 IEEE.published_or_final_versionThe 11th IEEE International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics '09), Huangshan, China, 19-21 August 2009. In Proceedings of 11th CAD/Graphics, 2009, p. 572-57

Computational network design from functional specifications

Connectivity and layout of underlying networks largely determine agent behavior and usage in many environments. For example, transportation networks determine the flow of traffic in a neighborhood, whereas building floorplans determine the flow of people in a workspace. Designing such networks from scratch is challenging as even local network changes can have large global effects. We investigate how to computationally create networks starting from only high-level functional specifications. Such specifications can be in the form of network density, travel time versus network length, traffic type, destination location, etc. We propose an integer programming-based approach that guarantees that the resultant networks are valid by fulfilling all the specified hard constraints and that they score favorably in terms of the objective function. We evaluate our algorithm in two different design settings, street layout and floorplans to demonstrate that diverse networks can emerge purely from high-level functional specifications

Rough paths in idealized financial markets

This paper considers possible price paths of a financial security in an idealized market. Its main result is that the variation index of typical price paths is at most 2, in this sense, typical price paths are not rougher than typical paths of Brownian motion. We do not make any stochastic assumptions and only assume that the price path is positive and right-continuous. The qualification "typical" means that there is a trading strategy (constructed explicitly in the proof) that risks only one monetary unit but brings infinite capital when the variation index of the realized price path exceeds 2. The paper also reviews some known results for continuous price paths and lists several open problems.Comment: 21 pages, this version adds (in Appendix C) a reference to new results in the foundations of game-theoretic probability based on Hardin and Taylor's work on hat puzzle

GN-SCCA: GraphNet based Sparse Canonical Correlation Analysis for Brain Imaging Genetics

Identifying associations between genetic variants and neuroimaging quantitative traits (QTs) is a popular research topic in brain imaging genetics. Sparse canonical correlation analysis (SCCA) has been widely used to reveal complex multi-SNP-multi-QT associations. Several SCCA methods explicitly incorporate prior knowledge into the model and intend to uncover the hidden structure informed by the prior knowledge. We propose a novel structured SCCA method using Graph constrained Elastic-Net (GraphNet) regularizer to not only discover important associations, but also induce smoothness between coefficients that are adjacent in the graph. In addition, the proposed method incorporates the covariance structure information usually ignored by most SCCA methods. Experiments on simulated and real imaging genetic data show that, the proposed method not only outperforms a widely used SCCA method but also yields an easy-to-interpret biological findings

Baseline predictors of remission, pain and fatigue in rheumatoid arthritis: the TITRATE trial.

BACKGROUND: Clinical trials show intensive treatment to induce remission is effective in patients with highly active rheumatoid arthritis (RA). The TITRATE trial showed that the benefits of intensive treatment also extend to moderately active RA. However, many patients failed to achieve remission or show improvements in pain and fatigue. We investigated whether baseline predictors could identify treatment non-responders. METHODS: The impact of obesity, depression, anxiety and illness perception on RA outcomes, including disease activity, remission, pain and fatigue were determined using a pre-planned secondary analysis of the TITRATE trial data. RESULTS: Body mass index was associated with disease activity levels and remission: obese patients had a higher overall disease activity and fewer obese patients achieved remission. Intensive management was not associated with increased remission in these patients. Obesity was also associated with increased overall pain and fatigue. Anxiety, depression and health perceptions had no discernible impact on disease activity but were associated with high levels of pain and fatigue. There was a strong association between anxiety and high pain scores; and between depression and high fatigue scores; and health perception was strongly related to both. None of the predictors had an important impact on pain and fatigue reduction in cross-sectional analysis. CONCLUSIONS: Disease activity is higher in obese patients and they have fewer remissions over 12 months. Anxiety, depression and health perceptions were associated with higher pain and fatigue scores. Intensive management strategies need to account for these baseline features as they impact significantly on clinical and psychological outcomes. TRIAL REGISTRATION: ISRCTN 70160382 ; date registered 16 January 2014

Preparation, structural characterisation and antibacterial properties of Ga-doped sol-gel phosphate-based glass

A sol-gel preparation of Ga-doped phosphate-based glass with potential application in antimicrobial devices has been developed. Samples of composition (CaO)(0.30)(Na2O)(0.20-x) (Ga2O3) (x) (P2O5)(0.50) where x = 0 and 0.03 were prepared, and the structure and properties of the gallium-doped sample compared with those of the sample containing no gallium. Analysis of the P-31 MAS NMR data demonstrated that addition of gallium to the sol-gel reaction increases the connectivity of the phosphate network at the expense of hydroxyl groups. This premise is supported by the results of the elemental analysis, which showed that the gallium-free sample contains significantly more hydrogen and by FTIR spectroscopy, which revealed a higher concentration of -OH groups in that sample. Ga K-edge extended X-ray absorption fine structure and X-ray absorption near-edge structure data revealed that the gallium ions are coordinated by six oxygen atoms. In agreement with the X-ray absorption data, the high-energy XRD results also suggest that the Ga3+ ions are octahedrally coordinated with respect to oxygen. Antimicrobial studies demonstrated that the sample containing Ga3+ ions had significant activity against Staphylococcus aureus compared to the control

SILAC-based proteomic quantification of chemoattractant-induced cytoskeleton dynamics on a second to minute timescale

Cytoskeletal dynamics during cell behaviours ranging from endocytosis and exocytosis to cell division and movement is controlled by a complex network of signalling pathways, the full details of which are as yet unresolved. Here we show that SILAC-based proteomic methods can be used to characterize the rapid chemoattractant-induced dynamic changes in the actin–myosin cytoskeleton and regulatory elements on a proteome-wide scale with a second to minute timescale resolution. This approach provides novel insights in the ensemble kinetics of key cytoskeletal constituents and association of known and novel identified binding proteins. We validate the proteomic data by detailed microscopy-based analysis of in vivo translocation dynamics for key signalling factors. This rapid large-scale proteomic approach may be applied to other situations where highly dynamic changes in complex cellular compartments are expected to play a key role

The Galaxy Structure-Redshift Relationship

There exists a gradual, but persistent, evolutionary effect in the galaxy population such that galaxy structure and morphology change with redshift. This galaxy structure-redshift relationship is such that an increasingly large fraction of all bright and massive galaxies at redshifts 2 < z < 3 are morphologically peculiar at wavelengths from rest-frame ultraviolet to rest-frame optical. There are however examples of morphologically selected spirals and ellipticals at all redshifts up to z ~ 3. At lower redshift, the bright galaxy population smoothly transforms into normal ellipticals and spirals. The rate of this transformation strongly depends on redshift, with the swiftest evolution occurring between 1 < z < 2. This review characterizes the galaxy structure-redshift relationship, discusses its various physical causes, and how these are revealing the mechanisms responsible for galaxy formation.Comment: 20 pages, 8 figures. Invited Review to appear in "Penetrating Bars Through Masks of Cosmic Dust: The Hubble Tuning Fork Strikes A New Note", ed. D. Block et a

Social interactions through the eyes of macaques and humans

Group-living primates frequently interact with each other to maintain social bonds as well as to compete for valuable resources. Observing such social interactions between group members provides individuals with essential information (e.g. on the fighting ability or altruistic attitude of group companions) to guide their social tactics and choice of social partners. This process requires individuals to selectively attend to the most informative content within a social scene. It is unclear how non-human primates allocate attention to social interactions in different contexts, and whether they share similar patterns of social attention to humans. Here we compared the gaze behaviour of rhesus macaques and humans when free-viewing the same set of naturalistic images. The images contained positive or negative social interactions between two conspecifics of different phylogenetic distance from the observer; i.e. affiliation or aggression exchanged by two humans, rhesus macaques, Barbary macaques, baboons or lions. Monkeys directed a variable amount of gaze at the two conspecific individuals in the images according to their roles in the interaction (i.e. giver or receiver of affiliation/aggression). Their gaze distribution to non-conspecific individuals was systematically varied according to the viewed species and the nature of interactions, suggesting a contribution of both prior experience and innate bias in guiding social attention. Furthermore, the monkeys’ gaze behavior was qualitatively similar to that of humans, especially when viewing negative interactions. Detailed analysis revealed that both species directed more gaze at the face than the body region when inspecting individuals, and attended more to the body region in negative than in positive social interactions. Our study suggests that monkeys and humans share a similar pattern of role-sensitive, species- and context-dependent social attention, implying a homologous cognitive mechanism of social attention between rhesus macaques and humans