Abstract Solar flares emit intense X‐ray and ultraviolet radiation, causing strong ionization in the neutral atmosphere and increasing the electron density in the ionospheric D‐region. These variations affect the propagation of very low frequency (VLF) radio signals, observed as perturbations in amplitude and phase. This study investigates the D‐region response to selected M and X‐class solar flares through VLF signal perturbation analysis. Data were recorded by a VLF receiver in Algeria (36.75N, 3.48E, Boumerdes), monitoring two transmitters (ICV and NSC) propagating over the Mediterranean Sea under similar conditions. The Long Wavelength Propagation Capability (LWPC) code was used to solve the inverse problem and derive Wait's parameters ( and ) and electron density variations. Nine flare events from the rising phase of Solar Cycle 24 (2011–2014) were analyzed, including eight M‐class and one X‐class flare. For the X2.8 flare on 13 May 2013, LWPC simulations showed that along the ICV–Algiers path, decreased from 74 to 54.71 km and increased from 0.3 to 0.485 . Along the NSC–Algiers path, decreased to 57.95 km and increased to 0.46 . These small differences are attributed to transmitter frequency. Averaging the results obtained from both paths improved electron density estimation. At 74 km, the electron density during the M1.0 flare increased from 216.10 to 2.9 × , while for the X2.8 flare it reached 91.3 × . Finally, ionization enhancement was simulated by solving the continuity equations using the Glukhov–Pasko–Inan model. The results are consistent with those derived from LWPC simulations.
Many different species of acidophilic prokaryotes, widely distributed within the domains Bacteria and Archaea, can catalyze the dissimilatory oxidation of ferrous iron or reduction of ferric iron, or can do both. Microbially mediated cycling of iron in extremely acidic environments (pH < 3) is strongly influenced by the enhanced chemical stability of ferrous iron and far greater solubility of ferric iron under such conditions. Cycling of iron has been demonstrated in vitro using both pure and mixed cultures of acidophiles, and there is considerable evidence that active cycling of iron occurs in acid mine drainage streams, pit lakes, and iron-rich acidic rivers, such as the Rio Tinto. Measurements of specific rates of iron oxidation and reduction by acidophilic microorganisms show that different species vary in their capacities for iron oxido-reduction, and that this is influenced by the electron donor provided and growth conditions used. These measurements, and comparison with corresponding data for oxidation of reduced sulfur compounds, also help explain why ferrous iron is usually used preferentially as an electron donor by acidophiles that can oxidize both iron and sulfur, even though the energy yield from oxidizing iron is much smaller than that available from sulfur oxidation. Iron-oxidizing acidophiles have been used in biomining (a technology that harness their abilities to accelerate the oxidative dissolution of sulfidic minerals and thereby facilitate the extraction of precious and base metals) for several decades. More recently they have also been used to simultaneously remediate iron-contaminated surface and ground waters and produce a useful mineral by-product (schwertmannite). Bioprocessing of oxidized mineral ores using acidophiles that catalyze the reductive dissolution of ferric iron minerals such as goethite has also recently been demonstrated, and new biomining technologies based on this approach are being developed.
Using the standard formalism of Lorentz transformation of the special theory of relativity, we derive the exact expression of the Thomas precession rate for an electron in a classical circular orbit around the nucleus of a hydrogen-like atom.
In the literature, there is an ambiguity in defining the relationship between trigonal and cubic symmetry classes of an elasticity tensor. We discuss the issue by examining the eigensystems and symmetry groups of trigonal and cubic tensors. Additionally, we present numerical examples indicating that the sole verification of the eigenvalues can lead to confusion in the identification of the elastic symmetry.