The effect of de Sitter like background on increasing the zero point budget of dark energy

During this work, using subtraction renormalization mechanism, zero point quantum fluctuations for bosonic scalar fields in a de-Sitter like background are investigated. By virtue of the observed value for spectral index, $n_s(k)$, for massive scalar field the best value for the first slow roll parameter, $\epsilon$, is achieved. In addition the energy density of vacuum quantum fluctuations for massless scalar field is obtained. The effects of these fluctuations on other components of the Universe are studied. By solving the conservation equation, for some different examples, the energy density for different components of the Universe are obtained. In the case which, all components of the Universe are in an interaction, the different dissipation functions, $\tilde{Q}_{i}$, are considered. The time evolution of ${\rho_{DE}(z)}/{\rho_{cri}(z)}$ shows that $\tilde{Q}=3 \gamma H(t) \rho_{m}$ has best agreement in comparison to observational data including CMB, BAO and SNeIa data set.Comment: 11 pages, 3 figure

Non-commutative and commutative vacua effects in a scalar torsion scenario

In this work, the effects of non-commutative and commutative vacua on the phase space generated by a scalar field in a scalar torsion scenario are investigated. For both classical and quantum regimes, the commutative and non-commutative cases are compared. To take account the effects of non-commutativity, two well known non-commutative parameters, $\theta$ and $\beta,$ are introduced. It should be emphasized, the effects of $\beta$ which is related to momentum sector has more key role in comparison to $\theta$ which is related to space sector. Also the different boundary conditions and mathematical interpretations of non-commutativity are explored.Comment: 10 pages, Accepted for publication in Physics Letters B (July/30/2015

An error-based variational approach to computational electromagnetics

Imperial Users onl

Gender differences in household headship and level of awareness on anaemia among Ethiopian women: Evidences from a nationwide cross-sectional survey

Background: Information on gender difference in household headship in relation to awareness and practice related to anaemia is limited. This study has examined the issue under caption and provides evidence-based information for some program initiatives.Methods: Data from 970 Ethiopian women of reproductive age was extracted from a large data set collected as part of a nation-wide micronutrient programmes surveillance to examine the association between gender difference in household-headship and anaemia awareness. Data were analysed in SPSS version 20.0 for Windows. Proportional differences on some selected variables were determined using χ2 test, and a p-value less than 0.05 was considered statistically significant.Results: Males were found to head more than two third of the households. Significantly lower number of respondents were less educated with just 140 (14.4%) having primary cycle education (grades 1-6th) (P=0.001). About half of the respondents (50.2%) were aware of anaemia, with at least two thirds of the respondents from male-headed households aware of its symptoms (p=0.004) and treatment (p=0.003), and the difference was significant. Fewer women received iron supplementation in female-headed households (28.6%) than male-headed households (71.4%), though the difference was not significant (p=0.9). Unexpectedly, significant number of respondents with low awareness was among those with primary education with some regional variations (p=0.001).Conclusion: Anaemia awareness and treatment seeking behaviour was markedly lower in female-headed households than male-headed households which can be attributed to low levels of education. Thus, to narrow the observed gap, targeted education programs for women headed household is recommended. [Ethiop. J. Health Dev. 2018; 32(2):75-81]Key words: Gender, education, anaemia, iron supplementation, women, Ethiopi

Interacting scalar tensor cosmology in light of SNeIa, CMB, BAO and OHD observational data sets

During this work, an interacting chameleon like scalar field scenario, by considering SNeIa, CMB, BAO and OHD data sets is investigated. In fact, the investigation is realized by introducing an ansatz for the effective dark energy equation of state, which mimics the behaviour of chameleon like models. Based on this assumption, some cosmological parameters including Hubble, deceleration and coincidence parameters in such mechanism are analysed. It is realized that, to estimate the free parameters of a theoretical model, by regarding the systematic errors it better the whole of the above observational data sets to be considered. In fact, if one considers SNeIa, CMB and BAO but disregards OHD it maybe leads to different results. Also to get a better overlap between the counters with the constraint $\chi _{\rm{m}}^2\leq 1$, the $\chi _{\rm{T}}^2$ function could be re-weighted. The relative probability functions are plotted for marginalized likelihood $\mathcal{L} (\Omega_{\rm{m0}} ,\omega_1, \beta)$ according to two dimensional confidence levels $68.3\%$, $90\%$ and $95.4\%$. Meanwhile, the value of free parameters which maximize the marginalized likelihoods using above confidence levels are obtained. In addition, based on these calculations the minimum value of $\chi^2$ based on free parameters of an ansatz for the effective dark energy equation of state are achieved.Comment: Accepted by the European Physical Journal C. 13 pages, 17 figures and 4 tables

A NOVEL SPECIALIZED SEARCH ENGINE FOR AI-MODELS AND THEIR COMPARISON

In recent years, the world of AI has tremendously increased in size and depth. Both new and old researchers are facing the problem of fast emerging AI researches, models and services. One needs to continuously read complete papers to understand the idea behind any novel research. This work presents a novel AI service that removes the burdens of long text reading and uncategorized search. It consists of a website that categorizes all the AI researches in a well-designed database. The users just have to select the models they are interested in, and the website will return a table containing the technical data in addition to a graph that shows visual relationships between the AI models, features and datasets. Future work will emphasize on developing the tool by applying NLP in two directions: one on the search box to retrieve the main keyword to search for, and the other on research papers to automatically extract the data into the website categorized database