Research on the Stability of a Rabbit Dry Eye Model Induced by Topical Application of the Preservative Benzalkonium Chloride

Dry eye is a common disease worldwide, and animal models are critical for the study of it. At present, there is no research about the stability of the extant animal models, which may have negative implications for previous dry eye studies. In this study, we observed the stability of a rabbit dry eye model induced by the topical benzalkonium chloride (BAC) and determined the valid time of this model.). Decreased levels of mucin-5 subtype AC (MUC5AC), along with histopathological and ultrastructural disorders of the cornea and conjunctiva could be observed in Group BAC-W4 and particularly in Group BAC-W5 until day 21.A stable rabbit dry eye model was induced by topical 0.1% BAC for 5 weeks, and after BAC removal, the signs of dry eye were sustained for 2 weeks (for the mixed type of dry eye) or for at least 3 weeks (for mucin-deficient dry eye)

Advances and Open Problems in Federated Learning

Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g. service provider), while keeping the training data decentralized. FL embodies the principles of focused data collection and minimization, and can mitigate many of the systemic privacy risks and costs resulting from traditional, centralized machine learning and data science approaches. Motivated by the explosive growth in FL research, this paper discusses recent advances and presents an extensive collection of open problems and challenges

Advances and Open Problems in Federated Learning

Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g. service provider), while keeping the training data decentralized. FL embodies the principles of focused data collection and minimization, and can mitigate many of the systemic privacy risks and costs resulting from traditional, centralized machine learning and data science approaches. Motivated by the explosive growth in FL research, this paper discusses recent advances and presents an extensive collection of open problems and challenges.Comment: Published in Foundations and Trends in Machine Learning Vol 4 Issue 1. See: https://www.nowpublishers.com/article/Details/MAL-08

Structure-activity of chelating depressants for chalcopyrite/pyrite separation: DFT study and flotation experiment

Three types of chelating depressants were studied for chalcopyrite/pyrite separation, including S-S, S-O, and O-O types, via density functional theory calculations and microflotation. The calculation results indicate that the depressant’s chelating atoms have large coefficient and great activity according to the molecular frontier orbital (HOMO and LUMO) and the orbital coefficients. For S-S type of depressant, S atom in both keto or enol forms won’t affect their HOMO and LUMO patterns and the orbital contributions. For S-O type, the presence of N atom in the ring structure of a molecular will increase the reactivity of O-Cu while weak S-Cu. For O-O type, the electron supply capacity of benzene ring is higher than strain chain, and atom N in strain chain increased their electron supply capacity. The microflotation results basically confirmed the prediction based on the calculation. The simulation results demonstrate that the interaction of a depressant with metals and minerals are affected obviously by the spatial structure and electronic structure of an atom in its molecular

Unusual Protonation of the Hydroxylammonium Cation Leading to the Low Thermal Stability of Hydroxylammonium-Based Salts

Energetic ionic salts (EISs) are a class of thriving and promising energetic materials (EMs) that can possess excellent properties and performances comparable to common conventional EMs composed of neutral molecules. As EMs, their response mechanisms to external stimuli are strongly responsible for their safety and thus are highly concerned about. Nevertheless, insight into these mechanisms remains still lacking. We find in the present work a bimolecular reaction between two same sign charged ions during heating dihydroxylammonium 5,5′-bistetrazole-1,1′-diolate (TKX-50), a typical EIS that are attracting increasing attention with a high potential of practical applications. That is, the protonation of NH₃OH⁺, or a reaction between two cations, occurs and serves as a dominant initial step in the thermal decay of TKX-50. This is a rare case as a bimolecular reaction can usually hardly take place between two ions with same sign charges (two anions or two cations), due to their electrostatic repulsion preventing their sufficient approaching each other to induce the reaction. The protonation proceeds by a H⁺ transfer from a NH₃OH⁺ to its neighboring one, and subsequently decompose NH₃OH⁺ to the final stable products of NH₃ and H₂O simultaneously to collapse the crystal lattice of TKX-50. This new finding can well explain the experimental observations of the prior decay of NH₃OH⁺ to the bistetrazole-1,1′-diolate anion when TKX-50 heated at a constant temperature of 190 °C and the relatively low thermal stability of NH₃OH⁺ based EISs relative to others. Thereby, we propose a strategy to avoid a ready proton transfer and subsequent decomposition to enhance the thermal stability of EISs. This work is hopefully to richen the insight into both the decay mechanism of EISs and the mechanism of the reactions between same sign charged ions