Variational Approximations in a Path-Integral Description of Potential Scattering

Using a recent path integral representation for the T-matrix in nonrelativistic potential scattering we investigate new variational approximations in this framework. By means of the Feynman-Jensen variational principle and the most general ansatz quadratic in the velocity variables -- over which one has to integrate functionally -- we obtain variational equations which contain classical elements (trajectories) as well as quantum-mechanical ones (wave spreading).We analyse these equations and solve them numerically by iteration, a procedure best suited at high energy. The first correction to the variational result arising from a cumulant expansion is also evaluated. Comparison is made with exact partial-wave results for scattering from a Gaussian potential and better agreement is found at large scattering angles where the standard eikonal-type approximations fail.Comment: 35 pages, 3 figures, 6 tables, Latex with amsmath, amssymb; v2: 28 pages, EPJ style, misprints corrected, note added about correct treatment of complex Gaussian integrals with the theory of "pencils", matches published versio

Increased upconversion performance for thin film solar cells a trimolecular composition

Photochemical upconversion based on triplet triplet annihilation TTA UC is employed to enhance the short circuit currents generated by two varieties of thin amp; 64257;lm solar cells, a hydrogenated amorphous silicon a Si H solar cell and a dye sensitized solar cell DSC . TTA UC is exploited to harvest transmitted sub bandgap photons, combine their energies and re radiate upconverted photons back towards the solar cells. In the present study we employ a dual emitter TTA UC system which allows for signi amp; 64257;cantly improved UC quantum yields as compared to the previously used single emitter TTA systems. In doing so we achieve record photo current enhancement values for both the a Si H device and the DSC, surpassing 10 3 mA cm 2 sun 2 for the amp; 64257;rst time for a TTA UC system and marking a record for upconversion enhanced solar cells in general. We discuss pertinent challenges of the TTA UC technology which need to be addressed in order to achieve its viable device application

Towards a glacial-sensitive model of island biogeography

Although the role that Pleistocene glacial cycles have played in shaping the present biota of oceanic islands world-wide has long been recognized, their geographical, biogeographical and ecological implications have not yet been fully incorporated within existing biogeographical models. Here we summarize the different types of impacts that glacial cycles may have had on oceanic islands, including cyclic changes in climate, shifts in marine currents and wind regimes and, especially, cycles of sea level change. The latter have affected geographical parameters such as island area, isolation and elevation. They have also influenced the configurations of archipelagos via island fusion and fission, and cycles of seamount emergence and submergence. We hypothesize that these sea level cycles have had significant impacts on the biogeographical processes shaping oceanic island biotas, influencing the rates and patterns of immigration and extinction and hence species richness. Here we provide a first step toward the development of a glacial-sensitive model of island biogeography, representing the tentative temporal evolution of those biogeographical parameters during the last glacial cycle. From this reasoning we attempt to derive predictions regarding the imprint of sea level cycles on genetic, demographic or biogeographical patterns within remote island biotas

Development of a High-Density Linkage Map and Tagging Leaf Spot Resistance in Pearl Millet Using Genotyping-by-Sequencing Markers

Pearl millet [Pennisetum glaucum (L.) R. Br; also Cenchrus americanus (L.) Morrone] is an important crop throughout the world but better genomic resources for this species are needed to facilitate crop improvement. Genome mapping studies are a prerequisite for tagging agronomically important traits. Genotyping-by-sequencing (GBS) markers can be used to build high-density linkage maps, even in species lacking a reference genome. A recombinant inbred line (RIL) mapping population was developed from a cross between the lines ‘Tift 99D2B1’ and ‘Tift 454’. DNA from 186 RILs, the parents, and the F1 was used for 96-plex ApeKI GBS library development, which was further used for sequencing. The sequencing results showed that the average number of good reads per individual was 2.2 million, the pass filter rate was 88%, and the CV was 43%. High-quality GBS markers were developed with stringent filtering on sequence data from 179 RILs. The reference genetic map developed using 150 RILs contained 16,650 single-nucleotide polymorphisms (SNPs) and 333,567 sequence tags spread across all seven chromosomes. The overall average density of SNP markers was 23.23 SNP/cM in the final map and 1.66 unique linkage bins per cM covering a total genetic distance of 716.7 cM. The linkage map was further validated for its utility by using it in mapping quantitative trait loci (QTLs) for flowering time and resistance to Pyricularia leaf spot [Pyricularia grisea (Cke.) Sacc.]. This map is the densest yet reported for this crop and will be a valuable resource for the pearl millet community

A simplified (modified) Duke Activity Status Index (M-DASI) to characterise functional capacity: A secondary analysis of the Measurement of Exercise Tolerance before Surgery (METS) study

Background Accurate assessment of functional capacity, a predictor of postoperative morbidity and mortality, is essential to improving surgical planning and outcomes. We assessed if all 12 items of the Duke Activity Status Index (DASI) were equally important in reflecting exercise capacity. Methods In this secondary cross-sectional analysis of the international, multicentre Measurement of Exercise Tolerance before Surgery (METS) study, we assessed cardiopulmonary exercise testing and DASI data from 1455 participants. Multivariable regression analyses were used to revise the DASI model in predicting an anaerobic threshold (AT) >11 ml kg −1 min −1 and peak oxygen consumption (VO 2 peak) >16 ml kg −1 min −1, cut-points that represent a reduced risk of postoperative complications. Results Five questions were identified to have dominance in predicting AT>11 ml kg −1 min −1 and VO 2 peak>16 ml.kg −1min −1. These items were included in the M-DASI-5Q and retained utility in predicting AT>11 ml.kg −1.min −1 (area under the receiver-operating-characteristic [AUROC]-AT: M-DASI-5Q=0.67 vs original 12-question DASI=0.66) and VO 2 peak (AUROC-VO2 peak: M-DASI-5Q 0.73 vs original 12-question DASI 0.71). Conversely, in a sensitivity analysis we removed one potentially sensitive question related to the ability to have sexual relations, and the ability of the remaining four questions (M-DASI-4Q) to predict an adequate functional threshold remained no worse than the original 12-question DASI model. Adding a dynamic component to the M-DASI-4Q by assessing the chronotropic response to exercise improved its ability to discriminate between those with VO 2 peak>16 ml.kg −1.min −1 and VO 2 peak<16 ml.kg −1.min −1. Conclusions The M-DASI provides a simple screening tool for further preoperative evaluation, including with cardiopulmonary exercise testing, to guide perioperative management

A study of CP violation in B-+/- -> DK +/- and B-+/- -> D pi(+/-) decays with D -> (KSK +/-)-K-0 pi(-/+) final states

A first study of CP violation in the decay modes B-+/- -> [(KSK +/-)-K-0 pi(-/+)](D)h(+/-) and B-+/- -> [(KSK +/-)-K-0 pi(-/+)](D)h(+/-), where h labels a K or pi meson and D labels a D-0 or (D) over bar (0) meson, is performed. The analysis uses the LHCb data set collected in pp collisions, corresponding to an integrated luminosity of 3 fb(-1). The analysis is sensitive to the CP-violating CKM phase gamma through seven observables: one charge asymmetry in each of the four modes and three ratios of the charge-integrated yields. The results are consistent with measurements of gamma using other decay modes

Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Measurement of ϒ production in pp collisions at √s = 2.76 TeV

The production of ϒ(1S), ϒ(2S) and ϒ(3S) mesons decaying into the dimuon final state is studied with the LHCb detector using a data sample corresponding to an integrated luminosity of 3.3 pb−1 collected in proton–proton collisions at a centre-of-mass energy of √s = 2.76 TeV. The differential production cross-sections times dimuon branching fractions are measured as functions of the ϒ transverse momentum and rapidity, over the ranges pT &#60; 15 GeV/c and 2.0 &#60; y &#60; 4.5. The total cross-sections in this kinematic region, assuming unpolarised production, are measured to be σ (pp → ϒ(1S)X) × B ϒ(1S)→μ+μ− = 1.111 ± 0.043 ± 0.044 nb, σ (pp → ϒ(2S)X) × B ϒ(2S)→μ+μ− = 0.264 ± 0.023 ± 0.011 nb, σ (pp → ϒ(3S)X) × B ϒ(3S)→μ+μ− = 0.159 ± 0.020 ± 0.007 nb, where the first uncertainty is statistical and the second systematic