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1.
Modeling of solvent role in protein folding experiments : dissertation
Knarik Yeritsyan, 2025, doctoral dissertation

Abstract: The Zimm-Bragg (ZB) model serves as a fundamental framework for elucidating conformational transitions in biopolymers, offering simplicity and efficacy in processing experimental data. This study provides a comprehensive review of the Zimm-Bragg model and its Hamiltonian formulation, with particular emphasis on incorporating water interactions and chain size effects into the computational framework. We propose a modified ZB model that accounts for water-polypeptide interactions, demonstrating its ability to describe phenomena such as cold denaturation and helix-coil transitions. In the realm of NanoBioTechnologies, the manipulation of short polypeptide chains is commonplace. Experimental investigation of these chains in vitro often relies on techniques like Circular Dichroism (CD) and timeresolved infrared spectroscopy. Determining interaction parameters necessitates processing the temperature dependence of the normalized degree of helicity through model fitting. Leveraging recent advancements in the Hamiltonian formulation of the Zimm and Bragg model, we explicitly incorporate chain length and solvent effects into the theoretical description. The resulting expression for helicity degree adeptly fits experimental data, yielding hydrogen bonding energies and nucleation parameter values consistent with field standards. Differential Scanning Calorimetry (DSC) stands as a potent tool for measuring the specific heat profile of materials, including proteins. However, relating the measured profile to microscopic properties requires a suitable model for fitting. We propose a novel algorithm for processing DSC experimental data based on the ZB theory of protein folding in water. This approach complements the classical two-state paradigm and provides insights into protein-water and intraprotein hydrogen bonding energies. An analytical expression for heat capacity, considering water interaction, is derived and successfully applied to fit numerous DSC experimental datasets reported in the literature. Additionally, we compare this approach with the classical two-state model, demonstrating its efficacy in fitting DSC data. Furthermore, we have developed and launched a free online tool for processing CD and DSC experimental data related to protein folding, aiming to support scientific research.
Keywords: Zimm-Bragg model, conformational transitions, helix-coil transitions, cold denaturation, circular dichroism, differential scanning calorimetry, protein folding, water-protein interaction, hydrogen bonding energy, degree of helicity, short polypeptide chains, protein heat capacity, protein data analysis, dissertations
Published in RUNG: 27.01.2025; Views: 246; Downloads: 9
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2.
Metal oxide interlayers for improved efficiency of solar energy conversion devices
Andraž Mavrič, Nadiia Pastukhova, Yanbo Li, 2024, published scientific conference contribution abstract

Keywords: thin films, metal oxide interlayers, solar energy conversion
Published in RUNG: 24.01.2025; Views: 232; Downloads: 1
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3.
Inference of the Mass Composition of Cosmic Rays with Energies from 10[sup]18.5 to 10[sup]20 eV Using the Pierre Auger Observatory and Deep Learning
A. Abdul Halim, Andrej Filipčič, Jon Paul Lundquist, Shima Ujjani Shivashankara, Samo Stanič, Serguei Vorobiov, Danilo Zavrtanik, Marko Zavrtanik, 2025, original scientific article

Abstract: We present measurements of the atmospheric depth of the shower maximum Xmax, inferred for the first time on an event-by-event level using the Surface Detector of the Pierre Auger Observatory. Using deep learning, we were able to extend measurements of the Xmax distributions up to energies of 100 EeV (10[sup]20 eV), not yet revealed by current measurements, providing new insights into the mass composition of cosmic rays at extreme energies. Gaining a 10-fold increase in statistics compared to the Fluorescence Detector data, we find evidence that the rate of change of the average Xmax with the logarithm of energy features three breaks at 6.5 ± 0.6 (stat) ± 1 (sys) EeV, 11 ± 2 (stat) ± 1 (sys) EeV, and 31 ± 5 (stat) ± 3 (sys) EeV, in the vicinity to the three prominent features (ankle, instep, suppression) of the cosmic-ray flux. The energy evolution of the mean and standard deviation of the measured Xmax distributions indicates that the mass composition becomes increasingly heavier and purer, thus being incompatible with a large fraction of light nuclei between 50 EeV and 100 EeV.
Keywords: ultra-high-energy cosmic rays (UHECRs), extensive air showers, Pierre Auger Observatory, UHECR mass composition, depth of the shower maximum, fluorescence detector, surface detector, deep learning
Published in RUNG: 20.01.2025; Views: 290; Downloads: 4
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4.
Measurement of the depth of maximum of air-shower profiles with energies between ▫$10^{18.5} and 10^{20}$▫ eV using the surface detector of the Pierre Auger Observatory and deep learning
A. Abdul Halim, P. Abreu, M. Aglietta, Andrej Filipčič, Jon Paul Lundquist, Shima Ujjani Shivashankara, Samo Stanič, Serguei Vorobiov, Danilo Zavrtanik, Marko Zavrtanik, 2025, original scientific article

Abstract: We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV (1 EeV = 10[sup]18 eV) using the distributions of the depth of shower maximum Xmax. The analysis relies on ∼50,000 events recorded by the surface detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the dataset offers a 10-fold increase in statistics with respect to fluorescence measurements at the Observatory. After cross-calibration using the fluorescence detector, this enables the first measurement of the evolution of the mean and the standard deviation of the Xmax distributions up to 100 EeV. Our findings are threefold: (i) The evolution of the mean logarithmic mass toward a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (ii) The evolution of the fluctuations of Xmax toward a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in Xmax at the highest energies. (iii) We find indications for a characteristic structure beyond a constant change in the mean logarithmic mass, featuring three breaks that are observed in proximity to the ankle, instep, and suppression features in the energy spectrum.
Keywords: ultra-high-energy cosmic rays, UHECRs, extensive air showers, Pierre Auger Observatory, UHECR mass composition, depth of shower maximum, fluorescence detector, surface detector, deep learning
Published in RUNG: 20.01.2025; Views: 299; Downloads: 4
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5.
Multi-messenger and transient astrophysics with the Cherenkov Telescope Array
Ž. Bošnjak, Anthony M. Brown, Alessandro Carosi, M. Chernyakova, Pierre Cristofari, F. Longo, A. López Oramas, M. Santander, Serguei Vorobiov, Danilo Zavrtanik, 2021, other component parts

Abstract: The discovery of gravitational waves, high-energy neutrinos or the very-high-energy counterpart of gamma-ray bursts has revolutionized the high-energy and transient astrophysics community. The development of new instruments and analysis techniques will allow the discovery and/or follow-up of new transient sources. We describe the prospects for the Cherenkov Telescope Array (CTA), the next-generation ground-based gamma-ray observatory, for multi-messenger and transient astrophysics in the decade ahead. CTA will explore the most extreme environments via very-high-energy observations of compact objects, stellar collapse events, mergers and cosmic-ray accelerators.
Keywords: multi-messenger astrophysics, gravitational waves, very-high-energy (VHE) gamma rays, cosmic rays, VHE neutrinos, transient astrophysical phenomena, Cherenkov Telescope Array Observatory
Published in RUNG: 13.01.2025; Views: 258; Downloads: 4
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6.
Probing extreme environments with the Cherenkov Telescope Array
C. Boisson, Anthony M. Brown, A. Burtovoi, M. Cerruti, M. Chernyakova, T. Hassan, J.-P. Lenain, Marina Manganaro, Serguei Vorobiov, Danilo Zavrtanik, 2021, other component parts

Abstract: The physics of the non-thermal Universe provides information on the acceleration mechanisms in extreme environments, such as black holes and relativistic jets, neutron stars, supernovae or clusters of galaxies. In the presence of magnetic fields, particles can be accelerated towards relativistic energies. As a consequence, radiation along the entire electromagnetic spectrum can be observed, and extreme environments are also the most likely sources of multi-messenger emission. The most energetic part of the electromagnetic spectrum corresponds to the very-high-energy (VHE, E>100 GeV) gamma-ray regime, which can be extensively studied with ground based Imaging Atmospheric Cherenkov Telescopes (IACTs). The results obtained by the current generation of IACTs, such as H.E.S.S., MAGIC, and VERITAS, demonstrate the crucial importance of the VHE band in understanding the non-thermal emission of extreme environments in our Universe. In some objects, the energy output in gamma rays can even outshine the rest of the broadband spectrum. The Cherenkov Telescope Array (CTA) is the next generation of IACTs, which, with cutting edge technology and a strategic configuration of ~100 telescopes distributed in two observing sites, in the northern and southern hemispheres, will reach better sensitivity, angular and energy resolution, and broader energy coverage than currently operational IACTs. With CTA we can probe the most extreme environments and considerably boost our knowledge of the non-thermal Universe.
Keywords: black holes, relativistic jets, neutron stars, supernovae, clusters of galaxies, particle acceleration mechanisms, very-high-energy gamma rays, Cherenkov Telescope Array Observatory
Published in RUNG: 10.01.2025; Views: 293; Downloads: 3
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7.
Origin and role of relativistic cosmic particles
A. Araudo, G. Morlino, B. Olmi, Fabio Acero, I. Agudo, Rémi Adam, Rafael Alves Batista, E. Amato, E. O. Angüner, Serguei Vorobiov, 2021, other component parts

Abstract: This white paper briefly summarizes the importance of the study of relativistic cosmic rays, both as a constituent of our Universe, and through their impact on stellar and galactic evolution. The focus is on what can be learned over the coming decade through ground-based gamma-ray observations over the 20 GeV to 300 TeV range. Submitted as input to ASTRONET Science Vision and Infrastructure roadmap on behalf of the CTA consortium.
Keywords: High Energy Astrophysical Phenomena, cosmic rays, supernova remnants, Cherenkov Telescope Array Observatory
Published in RUNG: 09.01.2025; Views: 308; Downloads: 4
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8.
Combined fit of spectrum and composition for FR0 radio-galaxy-emitted ultra–high energy cosmic rays with resulting secondary photons and neutrinos
Jon Paul Lundquist, Serguei Vorobiov, Lukas Merten, Anita Reimer, Margot Boughelilba, Paolo Da Vela, Fabrizio Tavecchio, Giacomo Bonnoli, Chiara Righi, 2025, original scientific article

Abstract: This study comprehensively investigates the gamma-ray dim population of Fanaroff–Riley Type 0 (FR0) radio galaxies as potentially significant sources of ultra–high energy cosmic rays (UHECRs, E > 10[sup]18 eV) detected on Earth. While individual FR0 luminosities are relatively low compared to the more powerful Fanaroff–Riley Type 1 and Type 2 galaxies, FR0s are substantially more prevalent in the local universe, outnumbering the more energetic galaxies by a factor of ∼5 within a redshift of z ≤ 0.05. Employing CRPropa3 simulations, we estimate the mass composition and energy spectra of UHECRs originating from FR0 galaxies for energies above 10[sup]18.6 eV. This estimation fits data from the Pierre Auger Observatory (Auger) using three extensive air shower models; both constant and energy-dependent observed elemental fractions are considered. The simulation integrates an approximately isotropic distribution of FR0 galaxies, extrapolated from observed characteristics, with UHECR propagation in the intergalactic medium, incorporating various plausible configurations of extragalactic magnetic fields, both random and structured. We then compare the resulting emission spectral indices, rigidity cutoffs, and elemental fractions with recent Auger results. In total, 25 combined energy-spectrum and mass-composition fits are considered. Beyond the cosmic-ray fluxes emitted by FR0 galaxies, this study predicts the secondary photon and neutrino fluxes from UHECR interactions with intergalactic cosmic photon backgrounds. The multimessenger approach, encompassing observational data and theoretical models, helps elucidate the contribution of low-luminosity FR0 radio galaxies to the total cosmic-ray energy density.
Keywords: ultra-high-energy cosmic rays, UHECRs, UHECR energy spectrum, Pierre Auger Observatory, UHECR mass composition, UHECR sources, extragalactic magnetic fields, UHECR propagation, CRPropa tool
Published in RUNG: 06.01.2025; Views: 318; Downloads: 6
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9.
Existing open data practices in high energy astro- and particle physics : lecture at the Mini workshop on Open Science, 6. 11. 2024, Ajdovščina
Serguei Vorobiov, 2024, unpublished conference contribution

Abstract: In this presentation, the existing open data practices in high energy astro-, particle and astroparticle physics are presented. Open data has become fundamental in astrophysics, particle, and astroparticle physics, enhancing collaboration, reproducibility, and transparency, while accelerating innovation. A recent shift toward openness, marked by data-sharing initiatives and accessible resources, is driving breakthroughs like the multi-messenger observation of GW170817, a neutron star merger detected in both gravitational waves and gamma rays, and the identification of blazar TXS 0506+056 as a high-energy neutrino source. Across these fields, robust efforts are underway to develop and implement FAIR-compliant data policies, with a wide array of supportive tools, standards, protocols, and software already in use (Virtual Observatory in astrophysics, CERN’s Open Data Portal in particle physics, ...). The challenges of astroparticle physics data, often more complex than traditional astrophysics or particle physics data, call for additional coordination and technical advancements to meet FAIR principles effectively. Machine learning also plays a transformative role in these domains, enhancing the analysis of both proprietary and open data to reveal new insights and optimize research methodologies.
Keywords: open data, FAIR data, astrophysics, high-energy particle physics, astroparticle physics, multi-messenger astronomy
Published in RUNG: 06.01.2025; Views: 306; Downloads: 1
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10.
Investigation of the potential of waste gasification systems in achieving sustainable waste management practices and exploring their potential to contribute to the circular economy : master's thesis
Anđela Korać, 2024, master's thesis

Abstract: Waste management is a global problem, as waste production continues to rise, and the methods used today, such as landfilling and incineration, can cause many environmental issues. Waste gasification, among other technologies, is a promising alternative since waste is turned into useful energy resources and reduces emissions with the formation of syngas. Thus, this thesis investigated the potential of waste gasification systems in sustainable waste management and circular economy. Focusing on its energy and economic potential, modeling methods were used to recreate real-world systems, with the goal of properly estimating the true sustainability potential of the waste gasification systems. Biomass gasification was evaluated through thorough thermodynamics and economic analysis. Although the initial calculations failed to provide positive results by showing the energy of 54 MJ, instead of the expected energy release, further analysis with the optimized conditions and different assumptions, provided more accurate results. By increasing the share of oxidized CO from 10% to 25%, and reducing the wet material from 35% to 10%, total released heat was estimated to be −148.9 MJ. With the right assumptions, the gasification process was proved to provide good energy values necessary for the sustainability of such a process. Additionally, the financial analysis produced a high Net Present Value (NPV) of EUR 3,434,411.46, Internal Rate of Return (IRR) of 21.81%, and a short payback period (PP) of 4.48 years, hence proving the strong economic potential and financial strength of such technology. Therefore, biomass waste gasification was concluded to be a positive investment opportunity with valuable long-term economic benefits, while still providing good energy balance.
Keywords: waste, gasification, energy, circular economy, emission
Published in RUNG: 18.12.2024; Views: 389; Downloads: 3
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