4,013 research outputs found
Statistical Shape Analysis using Kernel PCA
©2006 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
The electronic version of this article is the complete one and can be found online at: http://dx.doi.org/10.1117/12.641417DOI:10.1117/12.641417Presented at Image Processing
Algorithms and Systems, Neural Networks, and Machine Learning, 16-18 January 2006, San Jose, California, USA.Mercer kernels are used for a wide range of image and signal processing tasks like de-noising, clustering, discriminant analysis etc. These algorithms construct their solutions in terms of the expansions in a high-dimensional feature space F. However, many applications like kernel PCA (principal component analysis) can be used more effectively if a pre-image of the projection in the feature space is available. In this paper, we propose a novel method to reconstruct a unique approximate pre-image of a feature vector and apply it for statistical shape analysis. We provide some experimental results to demonstrate the advantages of kernel PCA over linear PCA for shape learning, which include, but are not limited to, ability to learn and distinguish multiple geometries of shapes and robustness to occlusions
<i>C-elegans</i> model identifies genetic modifiers of alpha-synuclein inclusion formation during aging
Inclusions in the brain containing alpha-synuclein are the pathological hallmark of Parkinson's disease, but how these inclusions are formed and how this links to disease is poorly understood. We have developed a <i>C-elegans</i> model that makes it possible to monitor, in living animals, the formation of alpha-synuclein inclusions. In worms of old age, inclusions contain aggregated alpha-synuclein, resembling a critical pathological feature. We used genome-wide RNA interference to identify processes involved in inclusion formation, and identified 80 genes that, when knocked down, resulted in a premature increase in the number of inclusions. Quality control and vesicle-trafficking genes expressed in the ER/Golgi complex and vesicular compartments were overrepresented, indicating a specific role for these processes in alpha-synuclein inclusion formation. Suppressors include aging-associated genes, such as sir-2.1/SIRT1 and lagr-1/LASS2. Altogether, our data suggest a link between alpha-synuclein inclusion formation and cellular aging, likely through an endomembrane-related mechanism. The processes and genes identified here present a framework for further study of the disease mechanism and provide candidate susceptibility genes and drug targets for Parkinson's disease and other alpha-synuclein related disorders
The prominent role of the heaviest fragment in multifragmentation and phase transition for hot nuclei
The role played by the heaviest fragment in partitions of multifragmenting
hot nuclei is emphasized. Its size/charge distribution (mean value,
fluctuations and shape) gives information on properties of fragmenting nuclei
and on the associated phase transition.Comment: 11 pages, Proceedings of IWND09, August 23-25, Shanghai (China
Portfolio selection problems in practice: a comparison between linear and quadratic optimization models
Several portfolio selection models take into account practical limitations on
the number of assets to include and on their weights in the portfolio. We
present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset
Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional
Value-at-Risk (LACVaR) models, where the assets are limited with the
introduction of quantity and cardinality constraints. We propose a completely
new approach for solving the LAM model, based on reformulation as a Standard
Quadratic Program and on some recent theoretical results. With this approach we
obtain optimal solutions both for some well-known financial data sets used by
several other authors, and for some unsolved large size portfolio problems. We
also test our method on five new data sets involving real-world capital market
indices from major stock markets. Our computational experience shows that,
rather unexpectedly, it is easier to solve the quadratic LAM model with our
algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of
the best commercial codes for mixed integer linear programming (MILP) problems.
Finally, on the new data sets we have also compared, using out-of-sample
analysis, the performance of the portfolios obtained by the Limited Asset
models with the performance provided by the unconstrained models and with that
of the official capital market indices
The Ctf18 RFC-like complex positions yeast telomeres but does not specify their replication time
Peer reviewedPreprin
Evaluating Promotional Approaches for Citizen Science Biological Recording: Bumblebees as a Group Versus Harmonia axyridis as a Flagship for Ladybirds
Over the past decade, the number of biological records submitted by members of the public have increased dramatically. However, this may result in reduced record quality, depending on how species are promoted in the media. Here we examined the two main promotional approaches for citizen science recording schemes: flagship-species, using one charismatic species as an umbrella for the entire group (here, Harmonia axyridis (Pallas) for Coleoptera: Coccinellidae), and general-group, where the group is promoted as a whole and no particular prominence is given to any one species (here, bumblebees, genus Bombus (Hymenoptera: Apidae)). Of the two approaches, the
general-group approach produced data that was not
biased towards any one species, but far fewer records
per year overall. In contrast, the flagship-species
approach generated a much larger annual dataset, but
heavily biased towards the flagship itself. Therefore,
we recommend that the approach for species promotion
is fitted to the result desired
Shallow water marine sediment bacterial community shifts along a natural CO2 gradient in the Mediterranean Sea off Vulcano, Italy.
The effects of increasing atmospheric CO(2) on ocean ecosystems are a major environmental concern, as rapid shoaling of the carbonate saturation horizon is exposing vast areas of marine sediments to corrosive waters worldwide. Natural CO(2) gradients off Vulcano, Italy, have revealed profound ecosystem changes along rocky shore habitats as carbonate saturation levels decrease, but no investigations have yet been made of the sedimentary habitat. Here, we sampled the upper 2 cm of volcanic sand in three zones, ambient (median pCO(2) 419 μatm, minimum Ω(arag) 3.77), moderately CO(2)-enriched (median pCO(2) 592 μatm, minimum Ω(arag) 2.96), and highly CO(2)-enriched (median pCO(2) 1611 μatm, minimum Ω(arag) 0.35). We tested the hypothesis that increasing levels of seawater pCO(2) would cause significant shifts in sediment bacterial community composition, as shown recently in epilithic biofilms at the study site. In this study, 454 pyrosequencing of the V1 to V3 region of the 16S rRNA gene revealed a shift in community composition with increasing pCO(2). The relative abundances of most of the dominant genera were unaffected by the pCO(2) gradient, although there were significant differences for some 5 % of the genera present (viz. Georgenia, Lutibacter, Photobacterium, Acinetobacter, and Paenibacillus), and Shannon Diversity was greatest in sediments subject to long-term acidification (>100 years). Overall, this supports the view that globally increased ocean pCO(2) will be associated with changes in sediment bacterial community composition but that most of these organisms are resilient. However, further work is required to assess whether these results apply to other types of coastal sediments and whether the changes in relative abundance of bacterial taxa that we observed can significantly alter the biogeochemical functions of marine sediments
Can We Really Prevent Suicide?
Every year, suicide is among the top 20 leading causes of death globally for all ages. Unfortunately, suicide is difficult to prevent, in large part because the prevalence of risk factors is high among the general population. In this review, clinical and psychological risk factors are examined and methods for suicide prevention are discussed. Prevention strategies found to be effective in suicide prevention
include means restriction, responsible media coverage, and general public education, as well identification methods such as screening, gatekeeper training, and primary care physician education. Although the treatment for preventing suicide is difficult, follow-up that includes pharmacotherapy, psychotherapy, or both may be useful. However, prevention methods cannot be restricted to the individual. Community, social, and policy interventions will also be essentia
Population studies of sporadic cerebral amyloid angiopathy and dementia: a systematic review.
BACKGROUND: Deposition of amyloid-beta (Abeta) in vessel walls of the brain as cerebral amyloid angiopathy (CAA) could be a major factor in the pathogenesis of dementia. Here we investigate the relationship between dementia and the prevalence of CAA in older populations. We searched the literature for prospective population-based epidemiological clinicopathological studies, free of the biases of other sampling techniques, which were used as a comparison. METHODS: To identify population-based studies assessing CAA and dementia, a previous systematic review of population-based clinicopathological studies of ageing and dementia was employed. To identify selected-sample studies, PsychInfo (1806-April Week 3 2008), OVID MEDLINE (1950-April Week 2 2008) and Pubmed (searched 21 April 2008) databases were searched using the term "amyloid angiopathy". These databases were also employed to search for any population-based studies not included in the previous systematic review. Studies were included if they reported the prevalence of CAA relative to a dementia classification (clinical or neuropathological). RESULTS: Four population-based studies were identified. They showed that on average 55-59% of those with dementia displayed CAA (of any severity) compared to 28-38% of the non-demented. 37-43% of the demented displayed severe CAA in contrast to 7-24% of the non-demented. There was no overlap in the range of these averages and they were less variable and lower than those reported in 38 selected sample studies (demented v non-demented: 32-100 v 0-77% regardless of severity; 0-50 v 0-11% for severe only). CONCLUSION: CAA prevalence in populations is consistently higher in the demented as compared to the non-demented. This supports a significant role for CAA in the pathogenesis of dementia
Bounds on 4D Conformal and Superconformal Field Theories
We derive general bounds on operator dimensions, central charges, and OPE
coefficients in 4D conformal and N=1 superconformal field theories. In any CFT
containing a scalar primary phi of dimension d we show that crossing symmetry
of implies a completely general lower bound on the central
charge c >= f_c(d). Similarly, in CFTs containing a complex scalar charged
under global symmetries, we bound a combination of symmetry current two-point
function coefficients tau^{IJ} and flavor charges. We extend these bounds to
N=1 superconformal theories by deriving the superconformal block expansions for
four-point functions of a chiral superfield Phi and its conjugate. In this case
we derive bounds on the OPE coefficients of scalar operators appearing in the
Phi x Phi* OPE, and show that there is an upper bound on the dimension of Phi*
Phi when dim(Phi) is close to 1. We also present even more stringent bounds on
c and tau^{IJ}. In supersymmetric gauge theories believed to flow to
superconformal fixed points one can use anomaly matching to explicitly check
whether these bounds are satisfied.Comment: 47 pages, 9 figures; V2: small corrections and clarification
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