A moving mesh finite element algorithm for the adaptive solution of time-dependent partial differential equations with moving boundaries

A moving mesh finite element algorithm is proposed for the adaptive solution of nonlinear diffusion equations with moving boundaries in one and two dimensions. The moving mesh equations are based upon conserving a local proportion, within each patch of finite elements, of the total “mass” that is present in the projected initial data. The accuracy of the algorithm is carefully assessed through quantitative comparison with known similarity solutions, and its robustness is tested on more general problems. Applications are shown to a variety of problems involving time-dependent partial differential equations with moving boundaries. Problems which conserve mass, such as the porous medium equation and a fourth order nonlinear diffusion problem, can be treated by a simplified form of the method, while problems which do not conserve mass require the full theory

Ti alloy with enhanced machinability in UAT turning

Metastable β-titanium alloys such as Ti 15V 3Al 3Cr 3Sn are of great technological interest thanks to their high fatigue strength-to-density ratio. However, their high hardness and poor machinability increase machining costs. Additionally, formation of undesirable long chips increases the machining time. To address those issues, a metastable β-titanium alloy (Ti 15V 3Al 3Cr 2Zr 0.9La) with enhanced machinability was developed to produce short chips even at low cutting speeds. A hybrid ultrasonically assisted machining technique, known to reduce cutting forces, was employed in this study. Cutting force components and surface quality of the finished work-pieces were analyzed for a range of cutting speeds in comparison with those for more traditional Ti 15V 3Al 3Cr 3Sn. The novel alloy demonstrated slightly improved machining characteristics at higher cutting speeds and is now ready for industrial applications

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Weber and church governance: religious practice and economic activity

The debate about the relationship between religion and economic activity in the wake of Weber has been cast largely in terms of belief and values. This article suggests an alternative focus on practice. It argues that taken for granted practices of church governance formed to-hand resources for the organization of economic activity. The argument is developed through an examination of the historical development of church governance practices in the Presbyterian Church of Scotland, with particular emphasis on the way in which theological belief gave rise to practices of accountability and record keeping. In turn such practices contributed to a ‘culture of organization’ which had implications for economic activity. A focus on governance practices can help to illuminate enduring patterns of difference in the organization of economic activity

RCW 49 at mid-infrared wavelengths: A glimpse from the Spitzer Space Telescope

The luminous, massive star formation region RCW 49, located in the southern Galactic plane, was imaged with the Infrared Array Camera (IRAC) on the Spitzer Space Telescope as part of the Galactic Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE) program. The IRAC bands contain polycyclic aromatic hydrocarbon (PAH) features at 3.3, 6.2, 7.7, and 8.6 μm, as well as the Brα line. These features are the major contributors to the diffuse emission from RCW 49 in the IRAC bands. The Spitzer IRAC images show that the dust in RCW 49 is distributed in a network of fine filaments, pillars, knots, sharply defined boundaries, bubbles, and bow shocks. The regions immediately surrounding the ionizing star cluster and W-R stars are evacuated of dust by stellar winds and radiation. The IRAC images of RCW 49 suggest that the dust in RCW 49 has been sculpted by the winds and radiation from the embedded luminous stars in the inner 5′ (inner ∼6 pc) of the nebula. At projected angular radii φ > 5′ from the central ionizing cluster, the azimuthally averaged infrared intensity falls off as ∼φ-3. Both high-resolution radio and mid-IR images suggest that the nebula is density bounded along its western boundary. The filamentary structure of the dust in RCW 49 suggests that the nebula has a small dust filling factor and, as a consequence, the entire nebula may be slightly density bounded to H-ionizing photons

Identification of main-sequence stars with mid-infrared excesses using glimpse: β pictoris analogs?

Spitzer IRAC 3.6-8 μm photometry obtained as part of the GLIMPSE survey has revealed mid-infrared excesses for 33 field stars with known spectral types in a 1.2 deg2 field centered on the southern Galactic H II region RCW 49. These stars comprise a subset of 184 stars with known spectral classification, most of which were preselected to have unusually red IR colors. We propose that the mid-IR excesses are caused by circumstellar dust disks that are either very late remnants of stellar formation or debris disks generated by planet formation. Of these 33 stars, 29 appear to be main-sequence stars on the basis of optical spectral classifications. Five of the 29 main-sequence stars are O or B stars with excesses that can be plausibly explained by thermal bremsstrahlung emission, and four are post-main-sequence stars. The lone O star is an O4 V((f)) at a spectrophotometric distance of 3233-535 +540 pc and may be the earliest member of the Westerlund 2 cluster. Of the remaining 24 main-sequence stars, 18 have spectral energy distributions that are consistent with hot dusty debris disks, a possible signature of planet formation. Modeling the excesses as blackbodies demonstrates that the blackbody components have fractional bolometric disk-to-star luminosity ratios, L IR/L*, ranging from 10-3 to 10-2 with temperatures ranging from 220 to 820 K. The inferred temperatures are more consistent with asteroid belts than with the cooler temperatures expected for Kuiper belts. Mid-IR excesses are found in all spectral types from late B to early K

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy