Energy-Momentum Distribution: Some Examples

In this paper, we elaborate the problem of energy-momentum in General Relativity with the help of some well-known solutions. In this connection, we use the prescriptions of Einstein, Landau-Lifshitz, Papapetrou and M\"{o}ller to compute the energy-momentum densities for four exact solutions of the Einstein field equations. We take the gravitational waves, special class of Ferrari-Ibanez degenerate solution, Senovilla-Vera dust solution and Wainwright-Marshman solution. It turns out that these prescriptions do provide consistent results for special class of Ferrari-Ibanez degenerate solution and Wainwright-Marshman solution but inconsistent results for gravitational waves and Senovilla-Vera dust solution.Comment: 20 pages, accepted for publication in Int. J. Mod. Phys.

Contribution of chronic conditions to the disability burden across smoking categories in middle-aged adults, Belgium

Introduction : Smoking is considered the single most important preventable cause of morbidity and mortality worldwide, contributing to increased incidence and severity of disabling conditions. The aim of this study was to assess the contribution of chronic conditions to the disability burden across smoking categories in middle-aged adults in Belgium. Methods : Data from 10,224 individuals aged 40 to 60 years who participated in the 1997, 2001, 2004, or 2008 Health Interview Surveys in Belgium were used. Smoking status was defined as never, former (cessation >= 2 years), former (cessation = 20 cigarettes/day). To attribute disability to chronic conditions, binomial additive hazards models were fitted separately for each smoking category adjusted for gender, except for former (cessation <2 years) and occasional light smokers due to the small sample size. Results : An increasing trend in the disability prevalence was observed across smoking categories in men (never = 4.8%, former (cessation >= 2 years) = 5.8%, daily light = 7.8%, daily heavy = 10.7%) and women (never = 7.6%, former (cessation >= 2 years) = 8.0%, daily light = 10.2%, daily heavy = 12.0%). Musculoskeletal conditions showed a substantial contribution to the disability burden in men and women across all smoking categories. Other important contributors were depression and cardiovascular diseases in never smokers; depression, chronic respiratory diseases, and diabetes in former smokers (cessation >= 2 years); chronic respiratory diseases, cancer, and cardiovascular diseases in daily light smokers; cardiovascular diseases and chronic respiratory diseases in men and depression and diabetes in women daily heavy smokers. Conclusions : Beyond the well-known effect of smoking on mortality, our findings showed an increasing trend of the disability prevalence and different contributors to the disability burden across smoking categories. This information can be useful from a public health perspective to define strategies to reduce disability in Belgium

Using Machine Learning Techniques to Support the Emergency Department

This research lays down foundations for a stronger presence of machine learning in the emergency department. Using machine learning to make predictions on a patient's situation can increase patient's health and decrease the waiting time. This paper explores to what extent it is possible to accurately predict ER outcome. These predictions will be based on routinely available ER data from a Dutch hospital. The data set used is representative for any Dutch Hospital. Prediction performance is compared between ML predictors. Using random forest and stacked ensemble gathered the best results. This research found that for more than half of the adult patients, the algorithm can very accurately predict hospitalization, with similar results for children and during the COVID-19. Moreover, it is investigated which characteristics and events contribute to the direction of the patient. Finally, several plans are introduced to substantially improve the ER process, for example by quickly reviewing patients selected by the algorithms. These might lead to an ER process that is significantly quicker, with more accurate diagnosis.</p

RNO 54: A Previously Unappreciated FU Ori Star

We present evidence in support of the hypothesis that the young stellar object RNO 54 is a mature-stage FU Ori type source. The star was first cataloged as a "red nebulous object" in the 1980s but appears to have undergone its outburst prior to the 1890s. Present-day optical and near-infrared spectra are consistent with those of other FU Ori-type stars, both in the details of spectral line presence and shape, and in the overall change in spectral type from an FGK-type in the optical, to the M-type presented in the near-infrared. In addition, the spectral energy distribution of RNO 54 is well-fit by a pure-accretion disk model with parameters: M = 10-3.45±0.06 M⊙ yr−1, M* = 0.23 ± 0.06 M⊙, and Rinner = 3.68 ± 0.76 R⊙, though we believe Rinner is likely close to its upper range of 4.5R⊙ in order to produce a Tmax = 7000K that is consistent with the optical to near-infrared spectra. The resulting Lacc is ∼265 L⊙. To find these values, we adopted a source distance d = 1400 pc and extinction AV = 3.9 mag, along with disk inclination i = 50 deg based on the consideration of confidence intervals from our initial disk model, and in agreement with observational constraints. The new appreciation of a well-known source as an FU Ori-type object suggests that other such examples may be lurking in extant samples

Together or not together:Paving the way to boundary crossing

The authors discuss how interprofessional education could ease the transition into collaborative practice by laying the foundation for interprofessional boundary crossing, suggesting that virtual IPE be used to nurture interprofessional feedback‐seeking behaviours

Self-organized patterns of coexistence out of a predator-prey cellular automaton

We present a stochastic approach to modeling the dynamics of coexistence of prey and predator populations. It is assumed that the space of coexistence is explicitly subdivided in a grid of cells. Each cell can be occupied by only one individual of each species or can be empty. The system evolves in time according to a probabilistic cellular automaton composed by a set of local rules which describe interactions between species individuals and mimic the process of birth, death and predation. By performing computational simulations, we found that, depending on the values of the parameters of the model, the following states can be reached: a prey absorbing state and active states of two types. In one of them both species coexist in a stationary regime with population densities constant in time. The other kind of active state is characterized by local coupled time oscillations of prey and predator populations. We focus on the self-organized structures arising from spatio-temporal dynamics of the coexistence. We identify distinct spatial patterns of prey and predators and verify that they are intimally connected to the time coexistence behavior of the species. The occurrence of a prey percolating cluster on the spatial patterns of the active states is also examined.Comment: 19 pages, 11 figure

Portal vein thrombosis in patients on the waiting list for liver transplantation : a single center cohort study

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