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Araujo Filho, A. A., Furtado, J., Hassanabadi, H., & Reis, J. A. A. S. (2023). Thermal analysis of photon-like particles in rainbow gravity. Phys. Dark Universe, 42, 101310–8pp.
Abstract: This work is devoted to study the thermodynamic behavior of photon-like particles within the rainbow gravity formalism. To to do this, we chose two particular ansatzs to accomplish our calculations. First, we consider a dispersion relation which avoids UV divergences, getting a positive effective cosmological constant. We provide numerical analysis for the thermodynamic functions of the system and bounds are estimated. Furthermore, a phase transition is also expected for this model. Second, we consider a dispersion relation employed in the context of Gamma Ray Bursts. Remarkably, for this latter case, the thermodynamic properties are calculated in an analytical manner and they turn out to depend on the harmonic series Hn, gamma & UGamma; (z), polygamma & psi;n(z) and zeta Riemann functions & zeta;(z).
Keywords: Rainbow gravity; Thermodynamics; Bounds
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Conde, D., Castillo, F. L., Escobar, C., García, C., Garcia Navarro, J. E., Sanz, V., et al. (2023). Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning. Space Weather, 21(11), e2023SW003474–27pp.
Abstract: Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests.
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Van Isacker, P., Algora, A., Vitéz-Sveiczer, A., Kiss, G. G., Orrigo, S. E. A., Rubio, B., et al. (2023). Gamow-Teller Beta Decay and Pseudo-SU(4) Symmetry. Symmetry-Basel, 15(11), 2001–15pp.
Abstract: We report on recent experimental results on beta decay into self-conjugate ( N = Z) nuclei with mass number 58 <= A <= 70. Super-allowed b decays from the J(pi) = 0(+) ground state of a Z = N + 2 parent nucleus are to the isobaric analogue state through so-called Fermi transitions and to J(pi) = 1(+) states by way of Gamow-Teller (GT) transitions. The operator of the latter decay is a generator of Wigner's SU(4) algebra and as a consequence GT transitions obey selection rules associated with this symmetry. Since SU(4) is progressively broken with increasing A, mainly as a consequence of the spinorbit interaction, this symmetry is not relevant for the nuclei considered here. We argue, however, that the pseudo-spin-orbit splitting can be small in nuclei with 58 <= A <= 70, in which case nuclear states exhibit an approximate pseudo-SU(4) symmetry. To test this conjecture, GT decay strength is calculated with use of a schematic Hamiltonian with pseudo-SU(4) symmetry. Some generic features of the GT beta decay due to pseudo-SU(4) symmetry are pointed out. The experimentally observed GT strength indicates a restoration of pseudo-SU(4) symmetry for A = 70.
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Weber, M. et al, & Esperante, D. (2024). DONES EVO: Risk mitigation for the IFMIF-DONES facility. Nucl. Mater. Energy, 38, 101622–5pp.
Abstract: The International Fusion Materials Irradiation Facility- DEMO Oriented Neutron Source (IFMIF-DONES) is a scientific infrastructure aimed to provide an intense neutron source for the qualification of materials to be used in future fusion power reactors. Its implementation is critical for the construction of the fusion DEMOnstration Power Plant (DEMO). IFMIF-DONES is a unique facility requiring a broad set of technologies. Although most of the necessary technologies have already been validated, there are still some aspects that introduce risks in the evolution of the project. In order to mitigate these risks, a consortium of companies, with the support of research centres and the funding of the CDTI (Centre for the Development of Industrial Technology and Innovation), has launched the DONES EVO Programme, which comprises six lines of research: center dot Improvement of signal transmission and integrity (planning and integration risks) center dot Optimisation of RF conditioning processes (planning and reliability risks) center dot Development of a reliable beam extraction device (reliability risks) center dot Development of technologies for the production of medical isotopes (reliability risks) center dot Improvement of critical parts of the lithium purification system (safety and reliability risks) center dot Validation of the manufacture of critical components with special materials (reliability risk). DONES EVO will focus on developing the appropriate response to the risks identified in the IFMIFDONES project through research and prototyping around the associated technologies.
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Di Gregorio, E., Staelens, M., Hosseinkhah, N., Karimpoor, M., Liburd, J., Lim, L., et al. (2024). Raman Spectroscopy Reveals Photobiomodulation-Induced α-Helix to β-Sheet Transition in Tubulins: Potential Implications for Alzheimer's and Other Neurodegenerative Diseases. Nanomaterials, 14(13), 1093–21pp.
Abstract: In small clinical studies, the application of transcranial photobiomodulation (PBM), which typically delivers low-intensity near-infrared (NIR) to treat the brain, has led to some remarkable results in the treatment of dementia and several neurodegenerative diseases. However, despite the extensive literature detailing the mechanisms of action underlying PBM outcomes, the specific mechanisms affecting neurodegenerative diseases are not entirely clear. While large clinical trials are warranted to validate these findings, evidence of the mechanisms can explain and thus provide credible support for PBM as a potential treatment for these diseases. Tubulin and its polymerized state of microtubules have been known to play important roles in the pathology of Alzheimer's and other neurodegenerative diseases. Thus, we investigated the effects of PBM on these cellular structures in the quest for insights into the underlying therapeutic mechanisms. In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm2 dose). Peaks in the Raman fingerprint region (300-1900 cm-1)-in particular, in the amide I band (1600-1700 cm-1)-were used to quantify the percentage of protein secondary structures. Under this band, hidden signals of C=O stretching, belonging to different structures, are superimposed, producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of polymerized NIR-exposed tubulin, characterized by a notable decrease in alpha-helix content and a concurrent increase in beta-sheets compared to the control samples. This PBM-induced alpha-helix to beta-sheet transition connects to reduced microtubule stability and the introduction of dynamism to allow for the remodeling and, consequently, refreshing of microtubule structures. This newly discovered mechanism could have implications for reducing the risks associated with brain aging, including neurodegenerative diseases like Alzheimer's disease, through the introduction of an intervention following this transition.
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