Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification of a shape prior using kernel density estimation is a natural technique. Unfortunately, energy functionals arising from kernel density estimation are of a form that makes them impossible to directly minimize using efficient optimization algorithms such as graph cuts. Our main contribution is to show how one may recast the energy functional into a form that is minimizable iteratively and efficiently using graph cuts.Comment: Revision submitted to JMIV (02/24/13

Improved protein structure prediction using potentials from deep learning

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence1. This problem is of fundamental importance as the structure of a protein largely determines its function2; however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures3. Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force4 that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction5 (CASP13)—a blind assessment of the state of the field—AlphaFold created high-accuracy structures (with template modelling (TM) scores6 of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined7

The Belt and Road Initiative for an intercontinental ecosystem: Strategic implications for multinational enterprises around the world

[Extract] International trade and foreign direct investment (FDI), as well as other forms of cross-border economic activities, are essential to globalization, even in the emerging era of neoglobalization as a unique balance between globalization and deglobalization. Despite the hype, globalization is a relatively new phenomenon

Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

We describe AlphaFold, the protein structure prediction system that was entered by the group A7D in CASP13 Submissions were made by three free-modelling methods which combine the predictions of three neural networks. All three systems were guided by predictions of distances between pairs of residues produced by a neural network. Two systems assembled fragments produced by a generative neural network, one using scores from a network trained to regress GDT_TS. The third system shows that simple gradient descent on a properly constructed potential is able to perform on-par with more expensive traditional search techniques and without requiring domain segmentation. In the CASP13 free-modelling assessors' ranking by summed z-scores, this system scored highest with 68.3 vs 48.2 for the next closest group. (An average GDT_TS of 61.4.) The system produced high-accuracy structures (with GDT_TS scores of 70 or higher) for 11 out of 43 free-modelling domains. Despite not explicitly using template information, the results in the template category were comparable to the best performing template-based methods

Thermal stability and diffusion in gadolinium silicate gate dielectric films

Gadolinium silicate films on Si(100) annealed in oxygen and vacuum at temperatures up to 800\u200a\ub0C were analyzed by Rutherford backscattering and narrow resonance nuclear profiling. Oxygen diffused into the film eliminating oxygen vacancies, but Si diffusion, previously observed in Al and Y oxides and in La and Zr silicate films, was absent. Higher-temperature annealing in oxygen resulted in the formation of an interfacial layer observable in high-resolution electron micrographs. Gd0.23Si0.14O0.63 films crystallize at temperatures between 1000 and 1050\u200a\ub0C. These observations combined with recent electrical measurements show that gadolinium silicate films may be a good candidate for the replacement of SiO2 in deep submicron metal\u2013oxide\u2013semiconductor gates.NRC publication: Ye

Scintillation Counters for the D0 Muon Upgrade

We present the results of an upgrade to the D0 muon system. Scintillating counters have been added to the existing central D0 muon system to provide rejection for cosmic ray muons and out-of-time background, and to provide additional fast timing information for muons in an upgraded Tevatron. Performance and results from the 1994-1996 Tevatron run are presented.Comment: 30 pages, 25 postscript figure

Partners and others: Social provisions and loneliness among married Dutch men and women in the second half of life.

Contains fulltext : 55911.pdf (publisher's version ) (Closed access)The main goal of this article was to test whether the perceived availability of social provisions within and outside marriage in a representative Dutch sample of men and women in late adulthood would differ from findings from similar studies in the United States. We predicted that there would be more similarity between married men and women in self-reported social relationships, social provisions, and loneliness in the more feminine culture of The Netherlands than is often reported in research from the United States, where the dominant culture is more masculine. Data are from the Dutch Aging survey that involved a representative sample of 983 people between the ages of 40 and 85. As predicted, we found similarity between men and women in the size and composition of core networks, the provision of emotional support to and from the partner, and in the provision of instrumental support to others. Contrary to our hypothesis, women exchanged more emotional support with friends, children, and other family and identified these persons more often as companions in leisure activities. Despite the women’s greater reported involvement in other relationships, these men were not lonelier than were women. For both men and women, social provisions from close relationships beyond the partner relation contributed to alleviating loneliness.22 p

GATE : a simulation toolkit for PET and SPECT

Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols, and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at the address http://www-lphe.epfl.ch/GATE/

Differential Production Cross Section of Z Bosons as a Function of Transverse Momentum at sqrt{s}=1.8 TeV

We present a measurement of the transverse momentum distribution of Z bosons produced in ppbar collisions at sqrt{s}=1.8 TeV using data collected by the D0 experiment at the Fermilab Tevatron Collider during 1994--1996. We find good agreement between our data and a current resummation calculation. We also use our data to extract values of the non-perturbative parameters for a particular version of the resummation formalism, obtaining significantly more precise values than previous determinations.Comment: 10 pages, 2 figures, submitted to Phys. Rev. Letters v2 has margin error correcte