1,267 research outputs found
Estimating total momentum at finite distances
We study the difficulties associated with the evaluation of the total Bondi
momentum at finite distances around the central source of a general
(asymptotically flat) spacetime. Since the total momentum is only rigorously
defined at future null infinity, both finite distance and gauge effects must be
taken into account for a correct computation of this quantity.
Our discussion is applicable in general contexts but is particularly relevant
in numerically constructed spacetimes for both extracting important physical
information and assessing the accuracy of additional quantities.Comment: 10 pages, 1 figure. Typos corrected. Comments added and a new
Appendix. To be published in PR
Modelling macronutrient dynamics in the Hampshire Avon river: a Bayesian approach to estimate seasonal variability and total flux
The macronutrients nitrate and phosphate are aquatic pollutants that arise naturally, however, in excess concentrations they can be harmful to human health and ecosystems. These pollutants are driven by river currents and show dynamics that are affected by weather patterns and extreme rainfall events. As a result, the nutrient budget in the receiving estuaries and coasts can change suddenly and seasonally, causing ecological damage to resident wildlife and fish populations. In this paper, we propose a statistical change-point model with interactions between time and river flow, to capture the macronutrient dynamics and their responses to river flow threshold behaviour. It also accounts for the nonlinear effect of water quality properties via nonparametric penalised splines. This model enables us to estimate the daily levels of riverine macronutrient fluxes and their seasonal and annual totals. In particular, we present a study of macronutrient dynamics on the Hampshire Avon River, which flows to the southern coast of the UK through the Christchurch Harbour estuary. We model daily data for more than a year during 2013-14 in which period there were multiple severe meteorological conditions leading to localised flooding. Adopting a Bayesian inference framework, we have quantified riverine macronutrient fluxes based on input river flow values. Out of sample empirical validation methods justify our approach, which captures also the dependencies of macronutrient concentrations with water body characteristics
Gravitational lens optical scalars in terms of energy-momentum distributions
This is a general work on gravitational lensing. We present new expressions
for the optical scalars and the deflection angle in terms of the
energy-momentum tensor components of matter distributions. Our work generalizes
standard references in the literature where normally stringent assumptions are
made on the sources. The new expressions are manifestly gauge invariant, since
they are presented in terms of curvature components. We also present a method
of approximation for solving the lens equations, that can be applied to any
order.Comment: 17 pages, 2 figures. Titled changed. Small improvements. References
added. Final version published in Phys.Rev.
Estimating weekly excess mortality at sub-national level in Italy during the COVID-19 pandemic
In this study we present the first comprehensive analysis of the spatio-temporal differences in excess mortality during the COVID-19 pandemic in Italy. We used a population-based design on all-cause mortality data, for the 7,904 Italian municipalities. We estimated sex-specific weekly mortality rates for each municipality, based on the first four months of 2016-2019, while adjusting for age, localised temporal trends and the effect of temperature. Then, we predicted all-cause weekly deaths and mortality rates at municipality level for the same period in 2020, based on the modelled spatio-temporal trends. Lombardia showed higher mortality rates than expected from the end of February, with 23,946 (23,013 to 24,786) total excess deaths. North-West and North-East regions showed one week lag, with higher mortality from the beginning of March and 6,942 (6,142 to 7,667) and 8,033 (7,061 to 9,044) total excess deaths respectively. We observed marked geographical differences also at municipality level. For males, the city of Bergamo (Lombardia) showed the largest percent excess, 88.9% (81.9% to 95.2%), at the peak of the pandemic. An excess of 84.2% (73.8% to 93.4%) was also estimated at the same time for males in the city of Pesaro (Central Italy), in stark contrast with the rest of the region, which does not show evidence of excess deaths. We provided a fully probabilistic analysis of excess mortality during the COVID-19 pandemic at sub-national level, suggesting a differential direct and indirect effect in space and time. Our model can be used to help policy-makers target measures locally to contain the burden on the health-care system as well as reducing social and economic consequences. Additionally, this framework can be used for real-time mortality surveillance, continuous monitoring of local temporal trends and to flag where and when mortality rates deviate from the expected range, which might suggest a second wave of the pandemic
Tetrads in SU(3) X SU(2) X U(1) Yang-Mills geometrodynamics
The relationship between gauge and gravity amounts to understanding
underlying new geometrical local structures. These structures are new tetrads
specially devised for Yang-Mills theories, Abelian and Non-Abelian in
four-dimensional Lorentzian spacetimes. In the present manuscript a new tetrad
is introduced for the Yang-Mills SU(3) X SU(2) X U(1) formulation. These new
tetrads establish a link between local groups of gauge transformations and
local groups of spacetime transformations. New theorems are proved regarding
isomorphisms between local internal SU(3) X SU(2) X U(1) groups and local
tensor products of spacetime LB1 and LB2 groups of transformations. The new
tetrads and the stress-energy tensor allow for the introduction of three new
local gauge invariant objects. Using these new gauge invariant objects and in
addition a new general local duality transformation, a new algorithm for the
gauge invariant diagonalization of the Yang-Mills stress-energy tensor is
developed.Comment: There is a new appendix. The unitary transformations by local SU(2)
subgroup elements of a local group coset representative is proved to be a new
local group coset representative. This proof is relevant to the study of the
memory of the local tetrad SU(3) generated gauge transformations. Therefore,
it is also relevant to the group theorems proved in the paper. arXiv admin
note: substantial text overlap with arXiv:gr-qc/060204
Estimating weekly excess mortality at sub-national level in Italy during the COVID-19 pandemic
In this study we present the first comprehensive analysis of the spatio-temporal differences in excess mortality during the COVID-19 pandemic in Italy. We used a population-based design on all-cause mortality data, for the 7,904 Italian municipalities. We estimated sex-specific weekly mortality rates for each municipality, based on the first four months of 2016-2019, while adjusting for age, localised temporal trends and the effect of temperature. Then, we predicted all-cause weekly deaths and mortality rates at municipality level for the same period in 2020, based on the modelled spatio-temporal trends. Lombardia showed higher mortality rates than expected from the end of February, with 23,946 (23,013 to 24,786) total excess deaths. North-West and North-East regions showed one week lag, with higher mortality from the beginning of March and 6,942 (6,142 to 7,667) and 8,033 (7,061 to 9,044) total excess deaths respectively. We observed marked geographical differences also at municipality level. For males, the city of Bergamo (Lombardia) showed the largest percent excess, 88.9% (81.9% to 95.2%), at the peak of the pandemic. An excess of 84.2% (73.8% to 93.4%) was also estimated at the same time for males in the city of Pesaro (Central Italy), in stark contrast with the rest of the region, which does not show evidence of excess deaths. We provided a fully probabilistic analysis of excess mortality during the COVID-19 pandemic at sub-national level, suggesting a differential direct and indirect effect in space and time. Our model can be used to help policy-makers target measures locally to contain the burden on the health-care system as well as reducing social and economic consequences. Additionally, this framework can be used for real-time mortality surveillance, continuous monitoring of local temporal trends and to flag where and when mortality rates deviate from the expected range, which might suggest a second wave of the pandemic
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