Stresses in the material with multilayered coating under impulse thermal loading

The two-dimensional model of mechanical behavior of the specimen with multi layered coating is formulated. The parametric analysis was carried out for various types of boundary conditions. Stress intensity depending on time was studied. The influence of impulse parameters on the temperature and stresses was investigated. It was revealed that radiation heat losses reduces the action of external loading

Microwave Schottky diagnostic systems for the Fermilab Tevatron, Recycler, and CERN LHC

A means for non-invasive measurement of transverse and longitudinal characteristics of bunched beams in synchrotrons has been developed based on high sensitivity slotted waveguide pickups. The pickups allow for bandwidths exceeding hundreds of MHz while maintaining good beam sensitivity characteristics. Wide bandwidth is essential to allow bunch-by-bunch measurements by means of a fast gate. The Schottky detector system is installed and successfully commissioned in the Fermilab Tevatron, Recycler and CERN LHC synchrotrons. Measurement capabilities include tune, chromaticity, and momentum spread of single or multiple beam bunches in any combination. With appropriate calibrations, emittance can also be measured by integrating the area under the incoherent tune sidebands

Statistical Communication Theory

Contains reports on seven research projects

Beam instrumentation for the Tevatron Collider

The Tevatron in Collider Run II (2001-present) is operating with six times more bunches and many times higher beam intensities and luminosities than in Run I (1992-1995). Beam diagnostics were crucial for the machine start-up and the never-ending luminosity upgrade campaign. We present the overall picture of the Tevatron diagnostics development for Run II, outline machine needs for new instrumentation, present several notable examples that led to Tevatron performance improvements, and discuss the lessons for future colliders

Sequence alignment, mutual information, and dissimilarity measures for constructing phylogenies

Existing sequence alignment algorithms use heuristic scoring schemes which cannot be used as objective distance metrics. Therefore one relies on measures like the p- or log-det distances, or makes explicit, and often simplistic, assumptions about sequence evolution. Information theory provides an alternative, in the form of mutual information (MI) which is, in principle, an objective and model independent similarity measure. MI can be estimated by concatenating and zipping sequences, yielding thereby the "normalized compression distance". So far this has produced promising results, but with uncontrolled errors. We describe a simple approach to get robust estimates of MI from global pairwise alignments. Using standard alignment algorithms, this gives for animal mitochondrial DNA estimates that are strikingly close to estimates obtained from the alignment free methods mentioned above. Our main result uses algorithmic (Kolmogorov) information theory, but we show that similar results can also be obtained from Shannon theory. Due to the fact that it is not additive, normalized compression distance is not an optimal metric for phylogenetics, but we propose a simple modification that overcomes the issue of additivity. We test several versions of our MI based distance measures on a large number of randomly chosen quartets and demonstrate that they all perform better than traditional measures like the Kimura or log-det (resp. paralinear) distances. Even a simplified version based on single letter Shannon entropies, which can be easily incorporated in existing software packages, gave superior results throughout the entire animal kingdom. But we see the main virtue of our approach in a more general way. For example, it can also help to judge the relative merits of different alignment algorithms, by estimating the significance of specific alignments.Comment: 19 pages + 16 pages of supplementary materia

Developing a pressure ulcer risk factor minimum data set and risk assessment framework

AIM: To agree a draft pressure ulcer risk factor Minimum Data Set to underpin the development of a new evidenced-based Risk Assessment Framework.BACKGROUND: A recent systematic review identified the need for a pressure ulcer risk factor Minimum Data Set and development and validation of an evidenced-based pressure ulcer Risk Assessment Framework. This was undertaken through the Pressure UlceR Programme Of reSEarch (RP-PG-0407-10056), funded by the National Institute for Health Research and incorporates five phases. This article reports phase two, a consensus study.DESIGN: Consensus study.METHOD: A modified nominal group technique based on the Research and Development/University of California at Los Angeles appropriateness method. This incorporated an expert group, review of the evidence and the views of a Patient and Public Involvement service user group. Data were collected December 2010-December 2011.FINDINGS: The risk factors and assessment items of the Minimum Data Set (including immobility, pressure ulcer and skin status, perfusion, diabetes, skin moisture, sensory perception and nutrition) were agreed. In addition, a draft Risk Assessment Framework incorporating all Minimum Data Set items was developed, comprising a two stage assessment process (screening and detailed full assessment) and decision pathways.CONCLUSION: The draft Risk Assessment Framework will undergo further design and pre-testing with clinical nurses to assess and improve its usability. It will then be evaluated in clinical practice to assess its validity and reliability. The Minimum Data Set could be used in future for large scale risk factor studies informing refinement of the Risk Assessment Framework

Changes in epithelial proportions and transcriptional state underlie major premenopausal breast cancer risks

The human breast undergoes lifelong remodeling in response to estrogen and progesterone, but hormone exposure also increases breast cancer risk. Here, we use single-cell analysis to identify distinct mechanisms through which breast composition and cell state affect hormone signaling. We show that prior pregnancy reduces the transcriptional response of hormone-responsive (HR+) epithelial cells, whereas high body mass index (BMI) reduces overall HR+ cell proportions. These distinct changes both impact neighboring cells by effectively reducing the magnitude of paracrine signals originating from HR+ cells. Because pregnancy and high BMI are known to protect against hormone-dependent breast cancer in premenopausal women, our findings directly link breast cancer risk with person-to-person heterogeneity in hormone responsiveness. More broadly, our findings illustrate how cell proportions and cell state can collectively impact cell communities through the action of cell-to-cell signaling networks