Strategy in context: the work and practice of New York's downtown artists in the late 1970s and early 1980s.

The rise of neo-conservatism defined the critical context of many appraisals of artistic work produced in downtown New York in the late 1970s and early 1980s. Although initial reviews of the scene were largely enthusiastic, subsequent assessments of artistic work from this period have been largely negative. Artists like Keith Haring, Jean-Michel Basquiat and Kenny Scharf have been assessed primarily in terms of gentrification, commodification, and political commitment relying upon various theoretical assumptions about social processes. The conclusions reached have primarily centred upon the lack of resistance by these artists to postindustrial capitalism in its various manifestations. My investigation engages in a debate with these texts by challenging these assumptions by which the downtown artists have been understood. I address the work of Richard Bolton, Suzi Gablik, Hal Foster and Craig Owens, amongst others, by critiquing their differing conceptions of structure and agency and introducing the analytical dualist approach of sociologist Margaret Archer, one which theorises the agency of social actors within social structures in a superior manner. After making my case, I investigate five economic and political conditions facing these artists, including corporate expansion, entrepreneurialism, the entertainment industry, the rise of the neo-conservative political agenda and the struggle for dominance amongst critics themselves. In each, I investigate the production and distribution practices of a wide range of downtown artists in relation to the historical context, from groups such as Colab and PADD to individuals including Ann Magnuson, David McDermott, Jenny Holzer, Richard Hambleton, John Fekner, Jane Dickson and David Wojnarowicz, in order to illuminate the relationship between such practices and the social structures which shaped such activity. In so doing, I conclude that artists were both constrained and enabled by these contexts, thus providing a more complex picture of their place in art history

Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles

The use of apps that record detailed menstrual cycle data presents a new opportunity to study the menstrual cycle. The aim of this study is to describe menstrual cycle characteristics observed from a large database of cycles collected through an app and investigate associations of menstrual cycle characteristics with cycle length, age and body mass index (BMI). Menstrual cycle parameters, including menstruation, basal body temperature (BBT) and luteinising hormone (LH) tests as well as age and BMI were collected anonymously from real-world users of the Natural Cycles app. We analysed 612,613 ovulatory cycles with a mean length of 29.3 days from 124,648 users. The mean follicular phase length was 16.9 days (95% CI: 10-30) and mean luteal phase length was 12.4 days (95% CI: 7-17). Mean cycle length decreased by 0.18 days (95% CI: 0.17-0.18, R2 = 0.99) and mean follicular phase length decreased by 0.19 days (95% CI: 0.19-0.20, R2 = 0.99) per year of age from 25 to 45 years. Mean variation of cycle length per woman was 0.4 days or 14% higher in women with a BMI of over 35 relative to women with a BMI of 18.5-25. This analysis details variations in menstrual cycle characteristics that are not widely known yet have significant implications for health and well-being. Clinically, women who wish to plan a pregnancy need to have intercourse on their fertile days. In order to identify the fertile period it is important to track physiological parameters such as basal body temperature and not just cycle length

Time to Pregnancy for Women Using a Fertility Awareness Based Mobile Application to Plan a Pregnancy

Background: Time to pregnancy (TTP) is a biomarker of fecundability and has been associated with behavioral and environmental characteristics; however, these associations have not been examined in a large population-based sample of application (app) users. Materials and Methods: This observational study followed 5,376 women with an age range of 18 to 45 years who used an app to identify their fertile window. We included women who started trying to conceive between September 30, 2017 and August 31, 2018. TTP was calculated as the number of menstrual cycles from when the user switched to "Plan" mode up to and including the cycle in which they logged a positive pregnancy test. We examined associations with several characteristics, including age, gravidity, body mass index, cycle length and cycle length variation, frequency of sexual intercourse, and temperature measuring frequency. Discrete time fecundability models were used to estimate fecundability odds ratios. Results: For the complete cohort the 6-cycle and 12-cycle cumulative pregnancy probabilities were found to be 61% (95% confidence interval [CI]: 59-62) and 74% (95% CI: 73-76), respectively. The median TTP was four cycles. The highest fecundability was associated with an age of less than 35 years, with cycle length variation <5 days and logging sexual intercourse on at least 20% of days added (the proportion of days in which intercourse was logged) (11.5% [n = 613] of entire sample). This group achieved a 6- and 12-cycle cumulative pregnancy probability of 88% (95% CI: 85-91) and 95% (95% CI: 94-97), respectively, and a TTP of 2 cycles. Conclusions: Natural Cycles was an effective method of identifying the fertile window and a noninvasive educational option for women planning a pregnancy. Women under age 35 with regular cycles showed a high pregnancy rate

Reversible Data Perturbation Techniques for Multi-level Privacy-preserving Data Publication

The amount of digital data generated in the Big Data age is increasingly rapidly. Privacy-preserving data publishing techniques based on differential privacy through data perturbation provide a safe release of datasets such that sensitive information present in the dataset cannot be inferred from the published data. Existing privacy-preserving data publishing solutions have focused on publishing a single snapshot of the data with the assumption that all users of the data share the same level of privilege and access the data with a fixed privacy level. Thus, such schemes do not directly support data release in cases when data users have different levels of access on the published data. While a straight-forward approach of releasing a separate snapshot of the data for each possible data access level can allow multi-level access, it can result in a higher storage cost requiring separate storage space for each instance of the published data. In this paper, we develop a set of reversible data perturbation techniques for large bipartite association graphs that use perturbation keys to control the sequential generation of multiple snapshots of the data to offer multi-level access based on privacy levels. The proposed schemes enable multi-level data privacy, allowing selective de-perturbation of the published data when suitable access credentials are provided. We evaluate the techniques through extensive experiments on a large real-world association graph dataset and our experiments show that the proposed techniques are efficient, scalable and effectively support multi-level data privacy on the published data

Does modafinil enhance activity of patients with myotonic dystrophy?: A double-blind placebo-controlled crossover study

We performed a double-blind placebo-controlled crossover study in 13 patients with myotonic dystrophy to address the question whether modafinil, known to improve hypersomnolence in myotonic dystrophy, may improve levels of activity as well. We used the Epworth Sleepiness Scale as a measure of hypersomnolence and a structured interview of the patient and the partner or housemate as a measure of activity. We additionally used a restricted form of the RAND-36 to relate a possible improvement of activity to perceived general health. We confirmed earlier positive findings of modafinil regarding reduced somnolence (p = 0.015), but no significant effects were seen regarding activity levels (p = 0.2 for patients’ self-reports and 0.5 for partners’ reports)

Rituximab for maintenance of remission in ANCA-associated vasculitis: expert consensus guidelines—Executive summary

[This is the executive summary of Rituximab for maintenance of remission in ANCA-associated vasculitis: expert consensus guidelines: full guideline, doi: 10.1093/rheumatology/kez640

Stellar winds from Massive Stars

We review the various techniques through which wind properties of massive stars - O stars, AB supergiants, Luminous Blue Variables (LBVs), Wolf-Rayet (WR) stars and cool supergiants - are derived. The wind momentum-luminosity relation (e.g. Kudritzki et al. 1999) provides a method of predicting mass-loss rates of O stars and blue supergiants which is superior to previous parameterizations. Assuming the theoretical sqrt(Z) metallicity dependence, Magellanic Cloud O star mass-loss rates are typically matched to within a factor of two for various calibrations. Stellar winds from LBVs are typically denser and slower than equivalent B supergiants, with exceptional mass-loss rates during giant eruptions Mdot=10^-3 .. 10^-1 Mo/yr (Drissen et al. 2001). Recent mass-loss rates for Galactic WR stars indicate a downward revision of 2-4 relative to previous calibrations due to clumping (e.g. Schmutz 1997), although evidence for a metallicity dependence remains inconclusive (Crowther 2000). Mass-loss properties of luminous (> 10^5 Lo) yellow and red supergiants from alternative techniques remain highly contradictory. Recent Galactic and LMC results for RSG reveal a large scatter such that typical mass-loss rates lie in the range 10^-6 .. 10^-4 Mo/yr, with a few cases exhibiting 10^-3 Mo/yr.Comment: 16 pages, 2 figures, Review paper to appear in Proc `The influence of binaries on stellar population studies', Brussels, Aug 2000 (D. Vanbeveren ed.), Kluwe

A new hammer to crack an old nut : interspecific competitive resource capture by plants is regulated by nutrient supply, not climate

Peer reviewedPublisher PD

Changes in socioeconomic inequality in Indonesian children's cognitive function from 2000 to 2007: a decomposition analysis

Background: Measuring social inequalities in health is common; however, research examining inequalities in child cognitive function is more limited. We investigated household expenditure-related inequality in children’s cognitive function in Indonesia in 2000 and 2007, the contributors to inequality in both time periods, and changes in the contributors to cognitive function inequalities between the periods. Methods: Data from the 2000 and 2007 round of the Indonesian Family Life Survey (IFLS) were used. Study participants were children aged 7–14 years (n = 6179 and n = 6680 in 2000 and 2007, respectively). The relative concentration index (RCI) was used to measure the magnitude of inequality. Contribution of various contributors to inequality was estimated by decomposing the concentration index in 2000 and 2007. Oaxaca-type decomposition was used to estimate changes in contributors to inequality between 2000 and 2007. Results: Expenditure inequality decreased by 45% from an RCI = 0.29 (95% CI 0.22 to 0.36) in 2000 to 0.16 (95% CI 0.13 to 0.20) in 2007 but the burden of poorer cognitive function was higher among the disadvantaged in both years. The largest contributors to inequality in child cognitive function were inequalities in per capita expenditure, use of improved sanitation and maternal high school attendance. Changes in maternal high school participation (27%), use of improved sanitation (25%) and per capita expenditures (18%) were largely responsible for the decreasing inequality in children’s cognitive function between 2000 and 2007. Conclusions: Government policy to increase basic education coverage for women along with economic growth may have influenced gains in children’s cognitive function and reductions in inequalities in Indonesia.Amelia Maika, Murthy N. Mittinty, Sally Brinkman, Sam Harper, Elan Satriawan, John W. Lync