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Shielding of a reactor is required for protection of people and environment during normal operation and accidental situations. In the present paper we investigated the shielding parameters viz. mass attenuation coefficients, linear attenuation coefficients, tenth-value layer, effective atomic numbers, kerma relative to air and exposure buildup factors for gamma-ray for ordinary, heavy, and super heavy concretes. Macroscopic effective removal cross-sections for fast neutron had also been calculated. Ordinary concrete is economically suitable for mixture high energy gamma-ray and neutron as it has large weight fraction of low-Z as compared with super heavy concretes to slow down the neutron. Super heavy concretes are superior shielding for both reactor operation and accident situations. The study is useful for optimizing for shielding design and radiation protection in the reactors.

Technology has enhanced the scope and span of the teaching and learning process but somehow it could not enhance the self-motivation and engagement among the students to the same scale. The lack of self-motivation and intermittent engagement is one of the prime challenges faced by educators today. Perplexing tasks for the faculty are to embroil students during the lecture. This work paves new ways to scale up the enticement using artificial intelligence and machine learning. The intelligent framework proposed here is built on yet another novel methodology used globally for user engagement and is termed gamification. The primary objective of the present research work is to negate the issue of disengagement by designing and implementing a gamified framework on 120 students from higher education that will include student engagement, enticement, and motivation. Generally, mechanisms are designed for specific courses, whereas the gamified system proposed is an open-ended method irrespective of course and the program being studied, and this framework has endeavored on multiple courses. To enhance the utility of the gamified framework, ANFIS model is utilized for smart decision-making concerning rewards distribution that is directly proportional to the number of coins gained by the students. As an outcome, better participation of a group of students under the proposed intelligent gamified system is reported as compared to the control group thus endorsing the success of the model.

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The inherently variable nature of renewable energy sources makes them storage-dependent when providing a reliable and continuous energy supply. One feasible energy-storage option that could meet this challenge is storing surplus renewable energy in the form of hydrogen. In this context, storage of hydrogen electrochemically in porous carbon-based electrodes is investigated. Measurements of hydrogen storage capacity, proton conductivity, and capacitance due to electrical double layer of several porous activated carbon electrodes are reported. The hydrogen storage capacity of the tested electrodes is found in the range of 0.61−1.05 wt.%, which compares favorably with commercially available metal hydride-based hydrogen storage, lithium polymer batteries, and lithium ion batteries in terms of gravimetric energy density. The highest obtained proton conductivity was 0.0965 S/cm, which is near to that of the commercial polymer-based proton conductor, nafion 117, under fully hydrated conditions. The obtained capacitance due to double-layers of the tested electrodes was in the range of 28.3–189.4 F/g. The relationship between specific surface area, micropore volume and hydrogen storage capacity of the carbon electrodes is discussed. The contribution of capacitance to the equivalent hydrogen storage capacity of carbon electrodes is reported. The implications of the obtained experimental results are discussed.

Abstract. We study the effect of neutrino degeneracy on primordial nucleosynthesis in a universe in which the cosmological scale factor evolves linearly with time. The degeneracy parameter of electron type neutrinos (ξ e ) determines the n/p (neutron to proton) ratio, which in turn determines the abundance of 4 He in a manner quite distinct from the Standard Scenario. The observed abundances of 4 He, Y P =0.254±0.003, and the minimum metallicity that is essential for fragmentation and cooling processes in star forming prestellar gas clouds (Z = Z cr = 10 −6 Z ), constrain the baryon to photon ratio, η B =(3.927±0.292)10 −9 , corresponding to a baryonic matter density, Ω B =0.263± 0.026 and ξ e =-2.165±0.171. This closes the dynamic mass estimates of matter in the universe, obtained from large scale velocity dispersion in galaxy clusters, by baryons alone. Useful byproducts are the threshold X(CNO) abundances required to trigger the CNO cycle in the observed low metallicity stars in the universe.arXiv:1312.7706v3 [astro-ph.CO] 30 May 2015

Low transition temperature mixtures (LTTMs) are versatile alternatives to ILs. They share many properties with ILs, so they become a suitable choice for entrainers in extractive distillation processes. In this study, glycolic acid and choline chloride in a 3:1 molar ratio (GC3:1) were synthesized and explored as entrainers for separation of acetonitrile + water azeotropic mixtures. Isobaric vapor−liquid equilibrium data for the pseudobinary mixtures of ACN + GC3:1 and water + GC3:1 were measured at atmospheric pressure (101.32 kPa). For the pseudoternary system ACN + water + GC3:1, also VLE data were measured at different GC3:1 mole fractions of 0.05, 0.1, and 0.15. The thermodynamic modeling of these systems was performed using the nonrandom two-liquid (NRTL) model. Furthermore, a study was conducted for synthesized GC3:1 recoverability. A good agreement were found between experimental data and predicted values for these systems. Results showed that LTTM (GC3:1) eliminated the acetonitrile + water azeotrope by manipulating the relative volatility of the acetonitrile + water mixture. Therefore, LTTM (GC3:1) can be concluded as an efficient entrainer for the separation of an acetonitrile + water azeotropic mixture by extractive distillation.