Ring Current Proton Decay Timescales Derived from Van Allen Probe Observations

The Earth's ring current is highly dynamic and is strongly influenced by the solar wind. The ring current alters the planet's magnetic field, defining geomagnetic storms. In this study, we investigate the decay timescales of ring current protons using observations from the Van Allen Probes. Since proton fluxes typically exhibit exponential decay after big storms, the decay time scales are calculated by performing linear regression on the logarithm of the fluxes. We found that in the central region of the ring current, proton decay timescales generally increase with increasing energies and increasing L-shells. The ~10s keV proton decay timescales are about a few days, while the ~100 keV proton decay time scale is about ~10 days, and protons of 269 keV have decay timescales up to ~118 days. These findings provide valuable insights into the ring current dynamics and can contribute to the development of more accurate ring current models.Comment: 8 pages, 7 figure

Boric Acid Cross-linked 3D Polyvinyl Alcohol Gel Beads by NaOH-Titration Method as a Suitable Biomass Immobilization Matrix

Granule-base immobilization of biomass is a potential method for a decent quality granular sludge cultivation. In this study, 3D polyvinyl alcohol (PVA) gel beads were chemically cross-linked via a simple NaOH-titration method. The PVA gel beads’ porous morphology was characterized using scanning electron microscope (SEM) and Brunauer–Emmette–Teller (BET), and their mechanical properties were evaluated by swelling rate and compressive stress tests. When cross-linking time was 10 min, high quality gel beads (P10) were synthesized, which demonstrated a homogeneous porous structure, good swelling rate, and high compressive strength. A mechanism for synthesis of the gel beads was proposed based on the results of Fourier transform infrared (FTIR) and X-ray diffractometer (XRD) analysis. Briefly, the intermolecular hydrogen bonds of PVA were firstly broken by NaOH to generate active bond of O–Na, which easily reacted with B(OH)4 − to produce the PVA-boric acid gel beads. P10 showed excellent biocompatibility for anaerobic ammonia oxidation (anammox) biomass’ immobilization. After incubation for three months, well granule-base immobilized sludge on P10 was developed in up-flow reactor. The sludge had high abundance of anammox biomass and was in balance with other functional bacteria. This work provides a simple method for the rapid preparation of 3D PVA gel beads and verifies their potential in granule-base immobilization of biomass.</p

Parallel multi-swarm cooperative particle swarm optimization for protein–ligand docking and virtual screening

BACKGROUND: A high-quality docking method tends to yield multifold gains with half pains for the new drug development. Over the past few decades, great efforts have been made for the development of novel docking programs with great efficiency and intriguing accuracy. AutoDock Vina (Vina) is one of these achievements with improved speed and accuracy compared to AutoDock4. Since it was proposed, some of its variants, such as PSOVina and GWOVina, have also been developed. However, for all these docking programs, there is still large room for performance improvement. RESULTS: In this work, we propose a parallel multi-swarm cooperative particle swarm model, in which one master swarm and several slave swarms mutually cooperate and co-evolve. Our experiments show that multi-swarm programs possess better docking robustness than PSOVina. Moreover, the multi-swarm program based on random drift PSO can achieve the best highest accuracy of protein–ligand docking, an outstanding enrichment effect for drug-like activate compounds, and the second best AUC screening accuracy among all the compared docking programs, but with less computation consumption than most of the other docking programs. CONCLUSION: The proposed multi-swarm cooperative model is a novel algorithmic modeling suitable for protein–ligand docking and virtual screening. Owing to the existing coevolution between the master and the slave swarms, this model in parallel generates remarkable docking performance. The source code can be freely downloaded from https://github.com/li-jin-xing/MPSOVina. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04711-0