A critical analysis of the hydrino model

Recently, spectroscopic and calorimetric observations of hydrogen plasmas and chemical reactions with them have been interpreted as evidence for the existence of electronic states of the hydrogen atom with a binding energy of more than 13.6 eV. The theoretical basis for such states, that have been dubbed hydrinos, is investigated. We discuss both, the novel deterministic model of the hydrogen atom, in which the existence of hydrinos was predicted, and standard quantum mechanics. Severe inconsistencies in the deterministic model are pointed out and the incompatibility of hydrino states with quantum mechanics is reviewed.Comment: 9 page

An investigation into the effect of thickness of titanium dioxide and gold-silver nanoparticle titanium dioxide composite thin-films on photocatalytic activity and photo-induced oxygen production in a sacrificial system

Thin films of titanium dioxide and titanium dioxide with incorporated gold and silver nanoparticles were deposited onto glass microscope slides, steel and titanium foil coupons by two sol–gel dip-coating methods. The film's photocatalytic activity and ability to evolve oxygen in a sacrificial solution were assessed. It was found that photocatalytic activity increased with film thickness (from 50 to 500 nm thick samples) for the photocatalytic degradation of methylene blue in solution and resazurin redox dye in an intelligent ink dye deposited on the surface. Contrastingly, an optimum film thickness of [similar]200 nm for both composite and pure films of titanium dioxide was found for water oxidation, using persulfate (S2O82−) as a sacrificial electron acceptor. The nanoparticle composite films showed significantly higher activity in oxygen evolution studies compared with plain TiO2 films

Substrate influence on the plasmonic response of clusters of spherical nanoparticles

The plasmonic response of nanoparticles is exploited in many subfields of science and engineering to enhance optical signals associated with probes of nanoscale and subnanoscale entities. We develop a numerical algorithm based on previous theoretical work that addresses the influence of a substrate on the plasmonic response of collections of nanoparticles of spherical shape. Our method is a real space approach within the quasi-static limit that can be applied to a wide range of structures. We illustrate the role of the substrate through numerical calculations that explore single nanospheres and nanosphere dimers fabricated from either a Drude model metal or from silver on dielectric substrates, and from dielectric spheres on silver substrates.Comment: 12 pages, 13 figure

Maternal age, development time, position effect variegation in Drosophila melanogaster

In Drosophila expression of position-effect variegation is enhanced by culturing flies at low temperatures. It is demonstrated that this effect may not be solely temperature dependent. Maternal age influences offspring development times. Futhermore, at a given temperature, the longer a fly takes to develop, the more likely is it to exhibit position-effect variegation.Chez la Drosophile, l’expression de la diversité de « l’effet position est favorisée lorsque les mouches se développent sous des températures basses. Il a été démontré que cet effet n’est pas uniquement dépendant de la température. L’âge maternel influence la durée de développement des descendants. De plus, pour une température donnée, il semble que plus la durée de développement est longue, plus l’expression de « l’effet position » est diversifiée

Quantum ratchet transport with minimal dispersion rate

We analyze the performance of quantum ratchets by considering the dynamics of an initially localized wave packet loaded into a flashing periodic potential. The directed center-of-mass motion can be initiated by the uniform modulation of the potential height, provided that the modulation protocol breaks all relevant time- and spatial reflection symmetries. A poor performance of quantum ratchet transport is characterized by a slow net motion and a fast diffusive spreading of the wave packet, while the desirable optimal performance is the contrary. By invoking a quantum analog of the classical P\'eclet number, namely the quotient of the group velocity and the dispersion of the propagating wave packet, we calibrate the transport properties of flashing quantum ratchets and discuss the mechanisms that yield low-dispersive directed transport.Comment: 6 pages; 3 figures; 1 tabl

Toward an understanding of optimal development environments within elite English soccer academies

This study examined the factors perceived by successful coaches to underpin optimal development environments within elite English soccer academies. A semistructured interview guide was developed to interview 10 expert coaches about the environments they create for players at a key stage in their development. The interviews were transcribed verbatim and inductively content analyzed. The results identified a wide range of factors resulting in a conceptual framework that explained how these factors interact to underpin an optimal environment. Subcomponents of this framework included organizational core (e.g., advocate a player-driven ideology), adaptability (e.g., embrace novel ideas & approaches), player welfare (e.g., understand players' world-view), key stakeholder relationships (e.g., build trust with parents), involvement (e.g., encourage players' ideas/feedback), and achievement oriented (e.g., establish an explicit pathway to senior level). Collectively, the findings highlight the importance of establishing strong, dynamic, organizational cultures at elite youth soccer academies. Ways that academies might be helped to establish such environments are discussed

Power management optimisation for hybrid electric systems using reinforcement learning and adaptive dynamic programming

This paper presents an online learning scheme based on reinforcement learning and adaptive dynamic programming for the power management of hybrid electric systems. Current methods for power management are conservative and unable to fully account for variations in the system due to changes in the health and operational conditions. These conservative schemes result in less efficient use of available power sources, increasing the overall system costs and heightening the risk of failure due to the variations. The proposed scheme is able to compensate for modelling uncertainties and the gradual system variations by adapting its performance function using the observed system measurements as reinforcement signals. The reinforcement signals are nonlinear and consequently neural networks are employed in the implementation of the scheme. Simulation results for the power management of an autonomous hybrid system show improved system performance using the proposed scheme as compared with a conventional offline dynamic programming approach