Catch crop strategy and nitrate leaching following grazed grass-clover

Cultivation of grassland presents a high risk of nitrate leaching. This study aimed to determine if leaching could be reduced by growing spring barley (Hordeum vulgare L.) as a green crop for silage with undersown Italian ryegrass (Lolium multiflorum Lam.) compared with barley grown to maturity with or without an undersown conventional catch crop of perennial ryegrass (Lolium perenne L.). All treatments received 0,60 or 120 kg of ammonium-N ha-1 in cattle slurry. In spring 2003, two grass-clover fields (3 and 5 years old, respectively, with different management histories) were ploughed. The effects of the treatments on yield and nitrate leaching were determined in the first year, while the residual effects of the treatments were determined in the second year in a crop of spring barley⁄perennial ryegrass. Nitrate leaching was estimated in selected treatments using soil water samples from ceramic cups. The experiment showed that compared with treatments without catch crop, green barley⁄Italian ryegrass reduced leaching by 163–320 kg Nha-1, corresponding to 95–99%, and the perennial ryegrass reduced leaching to between 34 and 86 kg Nha-1, corresponding to a reduction of 80 and 66%. Also, in the second growing season, leaching following catchcrops was reduced compared with the bare soil treatment. It was concluded that the green barley⁄Italian ryegrass offers advantages not only for the environment but also for farmers, for whom it provides a fodder high in roughage and avoids the difficulties with clover fatigue increasingly experienced by Danish farmers

Color superconducting quark matter core in the third family of compact stars

We investigate first order phase transitions from $\beta$-equilibrated hadronic matter to color flavor locked quark matter in compact star interior. The hadronic phase including hyperons and Bose-Einstein condensate of $K^-$ mesons is described by the relativistic field theoretical model with density dependent meson-baryon couplings. The early appearance of hyperons and/or Bose-Einstein condensate of $K^-$ mesons delays the onset of phase transition to higher density. In the presence of hyperons and/or $K^-$ condensate, the overall equations of state become softer resulting in smaller maximum masses than the cases without hyperons and $K^-$ condensate. We find that the maximum mass neutron stars may contain a mixed phase core of hyperons, $K^-$ condensate and color superconducting quark matter. Depending on the parameter space, we also observe that there is a stable branch of superdense stars called the third family branch beyond the neutron star branch. Compact stars in the third family branch may contain pure color superconducting core and have radii smaller than those of the neutron star branch. Our results are compared with the recent observations on RX J185635-3754 and the recently measured mass-radius relationship by X-ray Multi Mirror-Newton Observatory.Comment: 24 pages, RevTex, 9 figures included; section II shortened, section III elaborated, two new curves in Fig. 9 and acknowledgements added; version to bepublished in Phys. Rev.

Data visualization in yield component analysis: an expert study

Even though data visualization is a common analytical tool in numerous disciplines, it has rarely been used in agricultural sciences, particularly in agronomy. In this paper, we discuss a study on employing data visualization to analyze a multiplicative model. This model is often used by agronomists, for example in the so-called yield component analysis. The multiplicative model in agronomy is normally analyzed by statistical or related methods. In practice, unfortunately, usefulness of these methods is limited since they help to answer only a few questions, not allowing for a complex view of the phenomena studied. We believe that data visualization could be used for such complex analysis and presentation of the multiplicative model. To that end, we conducted an expert survey. It showed that visualization methods could indeed be useful for analysis and presentation of the multiplicative model

Paleobiology of titanosaurs: reproduction, development, histology, pneumaticity, locomotion and neuroanatomy from the South American fossil record

Fil: García, Rodolfo A.. Instituto de Investigación en Paleobiología y Geología. Museo Provincial Carlos Ameghino. Cipolletti; ArgentinaFil: Salgado, Leonardo. Instituto de Investigación en Paleobiología y Geología. General Roca. Río Negro; ArgentinaFil: Fernández, Mariela. Inibioma-Centro Regional Universitario Bariloche. Bariloche. Río Negro; ArgentinaFil: Cerda, Ignacio A.. Instituto de Investigación en Paleobiología y Geología. Museo Provincial Carlos Ameghino. Cipolletti; ArgentinaFil: Carabajal, Ariana Paulina. Museo Carmen Funes. Plaza Huincul. Neuquén; ArgentinaFil: Otero, Alejandro. Museo de La Plata. Universidad Nacional de La Plata; ArgentinaFil: Coria, Rodolfo A.. Instituto de Paleobiología y Geología. Universidad Nacional de Río Negro. Neuquén; ArgentinaFil: Fiorelli, Lucas E.. Centro Regional de Investigaciones Científicas y Transferencia Tecnológica. Anillaco. La Rioja; Argentin

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. Funding: Bill & Melinda Gates Foundation