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We sought to define the prevalence of echocardiographic abnormalities in long-term survivors of paediatric hematopoietic stem cell transplantation and determine the utility of screening in asymptomatic patients. We analysed echocardiograms performed on survivors who underwent hematopoietic stem cell transplantation from 1982 to 2006. A total of 389 patients were alive in 2017, with 114 having an echocardiogram obtained ⩾5 years post-infusion. A total of 95 patients had echocardiogram performed for routine surveillance. The mean time post-hematopoietic stem cell transplantation was 13 years. Of 95 patients, 77 (82.1%) had ejection fraction measured, and 10/77 (13.0%) had ejection fraction z-scores ⩽−2.0, which is abnormally low. Those patients with abnormal ejection fraction were significantly more likely to have been exposed to anthracyclines or total body irradiation. Among individuals who received neither anthracyclines nor total body irradiation, only 1/31 (3.2%) was found to have an abnormal ejection fraction of 51.4%, z-score −2.73. In the cohort of 77 patients, the negative predictive value of having a normal ejection fraction given no exposure to total body irradiation or anthracyclines was 96.7% at 95% confidence interval (83.3–99.8%). Systolic dysfunction is relatively common in long-term survivors of paediatric hematopoietic stem cell transplantation who have received anthracyclines or total body irradiation. Survivors who are asymptomatic and did not receive radiation or anthracyclines likely do not require surveillance echocardiograms, unless otherwise indicated.
Studies of Latin American civil society tend to assume that popular organizations promote “high-intensity” forms of political participation while political parties mainly encourage voting. This study compares the influence of these two forces in the urban informal sector. Association involvement, low in both samples, is related to “higher-intensity” participation, but the differential influence of associations and parties holds only for Costa Rica; Nicaragua’s revolutionary FSLN has fostered a more politically active citizenry.
The Neotoma Paleoecology Database is a community-curated data resource that supports interdisciplinary global change research by enabling broad-scale studies of taxon and community diversity, distributions, and dynamics during the large environmental changes of the past. By consolidating many kinds of data into a common repository, Neotoma lowers costs of paleodata management, makes paleoecological data openly available, and offers a high-quality, curated resource. Neotoma’s distributed scientific governance model is flexible and scalable, with many open pathways for participation by new members, data contributors, stewards, and research communities. The Neotoma data model supports, or can be extended to support, any kind of paleoecological or paleoenvironmental data from sedimentary archives. Data additions to Neotoma are growing and now include >3.8 million observations, >17,000 datasets, and >9200 sites. Dataset types currently include fossil pollen, vertebrates, diatoms, ostracodes, macroinvertebrates, plant macrofossils, insects, testate amoebae, geochronological data, and the recently added organic biomarkers, stable isotopes, and specimen-level data. Multiple avenues exist to obtain Neotoma data, including the Explorer map-based interface, an application programming interface, the neotoma R package, and digital object identifiers. As the volume and variety of scientific data grow, community-curated data resources such as Neotoma have become foundational infrastructure for big data science.
Among the important factors in the formation of melt water are: (1) The air and soil temperatures. (2) The presence or absence of debris on snow and ice. (3) The surface gradients of the glaciers. These gradients determine the areas of snow and ice in the zone where melting can occur as well as the amount of insolation. (4.) The orientation of snow and ice slopes. In general, in the Southern Hemisphere north-facing slopes receive more insolation than south-facing slopes.
The main source of the melt water is Wilson Piedmont Glacier, and the snowdrift-ice slabs are next in importance. The seasonal snowfall is not an important source, nor is the ice in the active zone. As no rain has ever been reported, all run-off is melt water.
The seasonal discharge of the Surko and Scheuren Rivers was roughly measured in 1957–58. It was found to be approximately 13 m3 s−1 d for the Surko River and approximately 19 m3 s−1 d for the Scheuren River, and it seems likely that the total seasonal discharge of all streams in the area was not far from 50 m3 s−1 d.
The anticipated release of EnlistTM cotton, corn, and soybean cultivars likely will increase the use of 2,4-D, raising concerns over potential injury to susceptible cotton. An experiment was conducted at 12 locations over 2013 and 2014 to determine the impact of 2,4-D at rates simulating drift (2 g ae ha−1) and tank contamination (40 g ae ha−1) on cotton during six different growth stages. Growth stages at application included four leaf (4-lf), nine leaf (9-lf), first bloom (FB), FB + 2 wk, FB + 4 wk, and FB + 6 wk. Locations were grouped according to percent yield loss compared to the nontreated check (NTC), with group I having the least yield loss and group III having the most. Epinasty from 2,4-D was more pronounced with applications during vegetative growth stages. Importantly, yield loss did not correlate with visual symptomology, but more closely followed effects on boll number. The contamination rate at 9-lf, FB, or FB + 2 wk had the greatest effect across locations, reducing the number of bolls per plant when compared to the NTC, with no effect when applied at FB + 4 wk or later. A reduction of boll number was not detectable with the drift rate except in group III when applied at the FB stage. Yield was influenced by 2,4-D rate and stage of cotton growth. Over all locations, loss in yield of greater than 20% occurred at 5 of 12 locations when the drift rate was applied between 4-lf and FB + 2 wk (highest impact at FB). For the contamination rate, yield loss was observed at all 12 locations; averaged over these locations yield loss ranged from 7 to 66% across all growth stages. Results suggest the greatest yield impact from 2,4-D occurs between 9-lf and FB + 2 wk, and the level of impact is influenced by 2,4-D rate, crop growth stage, and environmental conditions.
Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion and neuroticism traits. The NEO-FFI polygenic scores were used to predict life satisfaction in 7 cohorts, positive affect in 12 cohorts, and general wellbeing in 1 cohort (maximal N = 46,508). Meta-analysis of these results showed no significant association between NEO-FFI personality polygenic scores and the wellbeing measures. IRT extraversion and neuroticism polygenic scores were used to predict life satisfaction and positive affect in almost 37,000 individuals from UK Biobank. Significant positive associations (effect sizes <0.05%) were observed between the extraversion polygenic score and wellbeing measures, and a negative association was observed between the polygenic neuroticism score and life satisfaction. Furthermore, using GWA data, genetic correlations of -0.49 and -0.55 were estimated between neuroticism with life satisfaction and positive affect, respectively. The moderate genetic correlation between neuroticism and wellbeing is in line with twin research showing that genetic influences on wellbeing are also shared with other independent personality domains.
A number of socio-economic, biological and lifestyle characteristics change with advancing age and place very old adults at increased risk of micronutrient deficiencies. The aim of this study was to assess vitamin and mineral intakes and respective food sources in 793 75-year-olds (302 men and 491 women) in the North-East of England, participating in the Newcastle 85+ Study. Micronutrient intakes were estimated using a multiple-pass recall tool (2×24 h recalls). Determinants of micronutrient intake were assessed with multinomial logistic regression. Median vitamin D, Ca and Mg intakes were 2·0 (interquartile range (IQR) 1·2–6·5) µg/d, 731 (IQR 554–916) mg/d and 215 (IQR 166–266) mg/d, respectively. Fe intake was 8·7 (IQR 6·7–11·6) mg/d, and Se intake was 39·0 (IQR 27·3–55·5) µg/d. Cereals and cereal products were the top contributors to intakes of folate (31·5 %), Fe (49·2 %) and Se (46·7 %) and the second highest contributors to intakes of vitamin D (23·8 %), Ca (27·5 %) and K (15·8 %). More than 95 % (n 756) of the participants had vitamin D intakes below the UK’s Reference Nutrient Intake (10 µg/d). In all, >20 % of the participants were below the Lower Reference Nutrient Intake for Mg (n 175), K (n 238) and Se (n 418) (comparisons with dietary reference values (DRV) do not include supplements). As most DRV are not age specific and have been extrapolated from younger populations, results should be interpreted with caution. Participants with higher education, from higher social class and who were more physically active had more nutrient-dense diets. More studies are needed to inform the development of age-specific DRV for micronutrients for the very old.
The question of how modernity has influenced medievalism and how medievalism has influenced modernity is the theme of this volume. The opening essays examine the 2001 film Just Visiting's comments on modern anxieties via medievalism; conflations of modernity with both medievalism and the Middle Ages in rewriting sources; the emergence of modernity amid the post-World War I movement The MostNoble Order of Crusaders; António Sardinha's promotion of medievalism as an antidote to modernity; and Mercedes Rubio's medievalism in her feminist commentary on modernity. The eight subsequent articles build on this foundation while discussing remnants of medieval London amid its modern descendant; Michel Houellebecq's critique of medievalism through his 2011 novel La Carte et le territoire; historical authenticity in Michael Morrow's approach to performing medieval music; contemporary concerns in Ford Madox Brown and David Gentleman's murals; medieval Chester in Catherine A.M. Clarkeand Nayan Kulkarni's Hryre (2012); medieval influences on the formation of and debate about modern moral panics; medievalist considerations in modern repurposings of medieval anchorholds; andmedieval sources for Paddy Molloy's Here Be Dragons (2013). The articles thus test the essays' methods and conclusions, even as the essays offer fresh perspectives on the articles.
Karl Fugelso is Professor of Art History at Towson University in Baltimore, Maryland.
Contributors: Edward Breen, Katherine A. Brown, Catherine A.M. Clarke, Louise D'Arcens, Joshua Davies, John Lance Griffith, Mike Horswell, Pedro Martins, Paddy Molloy, Lisa Nalbone, Sarah Salih, Michelle M. Sauer, James L. Smith
The SMAC cluster sample (Hudson et al. 1999), with a depth of ˜ 12000km s-1, has a bulk velocity of ˜ 600 km s-1, with respect to the Cosmic Microwave Background (CMB) frame. Other surveys (Willick 1999, hereafter LP10k; Lauer & Postman 1994, hereafter ACIF) have also yielded large bulk motions on similarly large scales. Taken at face value, these results appear to be in conflict with bulk flows expected from favoured cosmological models. However, at the same time, other surveys (notably Dale et al. 1999, hereafter SC) have found rather small bulk motions on large scales. We have measured bulk flows from the above mentioned surveys plus SNIa (Riess et al. 1995) in a consistent way. The results are given in Table 1. The measurement errors are due to peculiar velocity errors. Note that these are the errors typically quoted. Based on these errors alone, there appears to be conflict between some of the surveys (e.g. SC vs SMAC).