Danceroom spectroscopy: At the frontiers of physics, performance, interactive art and technology

© 2016 ISAST. Danceroom Spectroscopy is an interactive audiovisual art installation and performance system driven by rigorous algorithms commonly used to simulate and analyze nanoscale atomic dynamics. danceroom Spectroscopy interprets humans as “energy landscapes,” resulting in an interactive system in which human energy fields are embedded within a simulation of thousands of atoms. Users are able to sculpt the atomic dynamics using their movements and experience their interactions visually and sonically in real time. danceroom Spectroscopy has so far been deployed as both an interactive sci-art installation and as the platform for a dance performance called Hidden Fields

Calls to a home birth helpline: empowerment in childbirth

In the UK a woman has the right to decide to give birth at home, irrespective of whether she is expecting her first or a subsequent child and of any perceived ‘risk’ factors. However, the rate of home births in the UK is very low (around 2%), varies widely across the country and many women do not know how to arrange midwifery cover. The Home Birth helpline is a UK-based voluntary organisation offering support and information for women planning a home birth. In order to gain direct access to the issues that are of concern to women when planning a home birth, 80 calls to the helpline were recorded. The aims of this paper are to document the problems that callers to this helpline report having when trying to arrange home births and to explore the strategies the call-taker uses in helping women to exercise their right to birth at home. The paper concludes that women are not easily able to exercise their right to choose the place of birth and suggests a number of recommendations for action

Biomass production of herbaceous energy crops in the United States: field trial results and yield potential maps from the multiyear regional feedstock partnership

Current knowledge of yield potential and best agronomic management practices for perennial bioenergy grasses is primarily derived from small‐scale and short‐term studies, yet these studies inform policy at the national scale. In an effort to learn more about how bioenergy grasses perform across multiple locations and years, the U.S. Department of Energy (US DOE)/Sun Grant Initiative Regional Feedstock Partnership was initiated in 2008. The objectives of the Feedstock Partnership were to (1) provide a wide range of information for feedstock selection (species choice) and management practice options for a variety of regions and (2) develop national maps of potential feedstock yield for each of the herbaceous species evaluated. The Feedstock Partnership expands our previous understanding of the bioenergy potential of switchgrass, Miscanthus, sorghum, energycane, and prairie mixtures on Conservation Reserve Program land by conducting long‐term, replicated trials of each species at diverse environments in the U.S. Trials were initiated between 2008 and 2010 and completed between 2012 and 2015 depending on species. Field‐scale plots were utilized for switchgrass and Conservation Reserve Program trials to use traditional agricultural machinery. This is important as we know that the smaller scale studies often overestimated yield potential of some of these species. Insufficient vegetative propagules of energycane and Miscanthus prohibited farm‐scale trials of these species. The Feedstock Partnership studies also confirmed that environmental differences across years and across sites had a large impact on biomass production. Nitrogen application had variable effects across feedstocks, but some nitrogen fertilizer generally had a positive effect. National yield potential maps were developed using PRISM‐ELM for each species in the Feedstock Partnership. This manuscript, with the accompanying supplemental data, will be useful in making decisions about feedstock selection as well as agronomic practices across a wide region of the country

Tissue-scale, personalized modeling and simulation of prostate cancer growth

Recently, mathematical modeling and simulation of diseases and their treatments have enabled the prediction of clinical outcomes and the design of optimal therapies on a personalized (i.e., patient-specific) basis. This new trend in medical research has been termed “predictive medicine.” Prostate cancer (PCa) is a major health problem and an ideal candidate to explore tissue-scale, personalized modeling of cancer growth for two main reasons: First, it is a small organ, and, second, tumor growth can be estimated by measuring serum prostate-specific antigen (PSA, a PCa biomarker in blood), which may enable in vivo validation. In this paper, we present a simple continuous model that reproduces the growth patterns of PCa. We use the phase-field method to account for the transformation of healthy cells to cancer cells and use diffusion-reaction equations to compute nutrient consumption and PSA production. To accurately and efficiently compute tumor growth, our simulations leverage isogeometric analysis (IGA). Our model is shown to reproduce a known shape instability from a spheroidal pattern to fingered growth. Results of our computations indicate that such shift is a tumor response to escape starvation, hypoxia, and, eventually, necrosis. Thus, branching enables the tumor to minimize the distance from inner cells to external nutrients, contributing to cancer survival and further development. We have also used our model to perform tissue-scale, personalized simulation of a PCa patient, based on prostatic anatomy extracted from computed tomography images. This simulation shows tumor progression similar to that seen in clinical practice.Peer ReviewedPostprint (published version