109 research outputs found
Shape Space Methods for Quantum Cosmological Triangleland
With toy modelling of conceptual aspects of quantum cosmology and the problem
of time in quantum gravity in mind, I study the classical and quantum dynamics
of the pure-shape (i.e. scale-free) triangle formed by 3 particles in 2-d. I do
so by importing techniques to the triangle model from the corresponding 4
particles in 1-d model, using the fact that both have 2-spheres for shape
spaces, though the latter has a trivial realization whilst the former has a
more involved Hopf (or Dragt) type realization. I furthermore interpret the
ensuing Dragt-type coordinates as shape quantities: a measure of
anisoscelesness, the ellipticity of the base and apex's moments of inertia, and
a quantity proportional to the area of the triangle. I promote these quantities
at the quantum level to operators whose expectation and spread are then useful
in understanding the quantum states of the system. Additionally, I tessellate
the 2-sphere by its physical interpretation as the shape space of triangles,
and then use this as a back-cloth from which to read off the interpretation of
dynamical trajectories, potentials and wavefunctions. I include applications to
timeless approaches to the problem of time and to the role of uniform states in
quantum cosmological modelling.Comment: A shorter version, as per the first stage in the refereeing process,
and containing some new reference
Processing of aluminum-graphite particulate metal matrix composites by advanced shear technology
Copyright @ 2009 ASM International. This paper was published in Journal of Materials Engineering and Performance 18(9) and is made available as an electronic reprint with the permission of ASM International. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplications of any material in this paper for a fee or for commercial purposes, or modification of the content of this paper are prohibited.To extend the possibilities of using aluminum/graphite composites as structural materials, a novel process is developed. The conventional methods often produce agglomerated structures exhibiting lower strength and ductility. To overcome the cohesive force of the agglomerates, a melt conditioned high-pressure die casting
(MC-HPDC) process innovatively adapts the well-established, high-shear dispersive mixing action of a twin screw mechanism. The distribution of particles and properties of composites are quantitatively evaluated.
The adopted rheo process significantly improved the distribution of the reinforcement in the matrix with a strong interfacial bond between the two. A good combination of improved ultimate tensile strength (UTS) and tensile elongation (e) is obtained compared with composites produced by conventional processes.EPSR
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
Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimerâs Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-ÎČ PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimerâs Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-ÎČ positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimerâs disease-related phenotypes, including measures of cognition or brain Amyloid-ÎČ burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes
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
Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference
The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18
7 10 124 ) or temporal stage (p = 3.96
7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine
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
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