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Ecological and geological systems formed on massifs of coarse clastic soils have a number of characteristic features of both abiotic components (lithotope, edaphotope) and biotic (microbocenosis, phyto- and zoocenosis). It has been revealed that the structure and functioning of these ecological and geological systems (EGS) are largely determined by the features of their lithotope – complexly built massifs of coarse clastic soils with a certain genesis (relating to the eluvial, water, glacial, slope or volcanogenic-sedimentary series), geological structure, relief and exogenous geological processes developed within these massifs. The main features of the EGS lithotope of the coarse-grained soil massif include the following: 1) discrete structure of the massif due to rock fragments of different sizes; 2) the shape of the debris; 3) the presence and features of the porous filler; 4) chemical and mineral composition of fragments; 5) soil salinity; 6) geochemical migration of substances; 7) physical and mechanical properties of the soil; 8) soil weathering; 9) its water cut; 10) expressiveness in relief; 11) paragenesis of modern exogenous geological processes (weathering, erosion, cryogenic processes, as well as slope gravitational processes: landslides, screes, stone avalanches, etc.). This abiotic component affects both the formation of soils and the formation of microbiocenoses, phyto- and zoocenoses developed within these systems. The features of a specific ecological-geological system of a coarse-clastic soil massif are considered on the example of the Big and Small Iremel mountains in the Southern Urals (Republic of Bashkortostan), whose specific biocenosis is characterized by a boreal mountain-taiga type. Scale-type epilithic lichens play an important role in the formation of their phytocenoses.

The concept of a quasi-absolutely continuous function on a closed interval of functions is introduced and a condition for the compactness of a set in the space of quasi-absolutely continuous functions on a closed interval is obtained.

Chromatin repair assembly is an important step in maintaining genome stability. The correct assembly of chromatin is provided by histone chaperones, whose dysfunction can lead to the development of various forms of cancer and a number of hereditary diseases in humans. The effect of remodeling factors completes chromatin repair. The yeast chromatin remodeling complex INO80 plays an important role in chromatin architecture. We used induced mutagenesis and real-time PCR to study the role of INO80 in chromatin repair assembly. In double mutants ies5Δ hsm3Δ (hif1Δ), defects in the structure of nucleosomes caused by mutations hsm3Δ and hif1Δ lead to hypersensitivity of cells to UV radiation and the disappearance of hsm3- and hif1-specific mutagenesis. Double mutants carrying the nhp10Δ mutation and hsm3Δ or hif1Δ mutations were indistinguishable from a single mutant in terms of the lethal effect of UV irradiation, but the high UV-induced mutagenesis characteristic of all mutations disappeared. Thus, it gas been found that mutations in the genes controlling the subunits of the INO80 complex can exhibit strong interactions with mutations in histone chaperone genes. The hypothesis that the Him1 protein performs a chaperone function in the process of chromatin repair assembly has been confirmed. [ABSTRACT FROM AUTHOR]

This work continues the earlier studies focusing on fabrication of heterophase micropowders and consolidated ceramics based on HfB2–HfC–SiC ultra-high-temperature boride/carbide compositions via self-propagating high-temperature synthesis (SHS) and hot pressing (HP). The effect of NH4Cl addition on the morphology and microstructure of the SHS powders was studied. Composite micropowders characterized by particle size of 0.2–10 μm and 40–50% content of the submicron-sized fraction were fabricated. The structure, mechanical and thermophysical properties, kinetics and mechanism of high-temperature oxidation of hot-pressed ceramic materials composed of 57–72 wt % HfB2, 14–20 wt % HfCx, 10–14 wt % SiC, and 8–15 wt % HfO2 were studied. They are found to have hardness up to 18.9 GPa, crack resistance up to 9.7 MPa m0.5, bending strength up to 400 MPa, temperature diffusivity up to 22.6 mm2/s, and thermal conductivity up to 59 W/(m K). The power law describes their oxidation kinetics. The protection mechanism against oxidation involves the formation of a multilayered heterogenous oxide film consisting of HfO2, HfSiO4, and borosilicate glass. [ABSTRACT FROM AUTHOR]

Thiram is a dithiocarbamate derivative, which is used as a fungicide for seed dressing and spraying during the vegetation period of plants, and also as an active vulcanization accelerator in the production of rubber-based rubber products. In this study the content of reactive oxygen species (ROS) and the state of the glutathione system have been investigated in the oral fluid and gum tissues of adult male Wistar rats treated with thiram for 28 days during its administration with food at a dose of 1/50 LD50. Thiram induced formation of ROS in the oral cavity; this was accompanied by an imbalance in the ratio of reduced and oxidized forms of glutathione due to a decrease in glutathione and an increase in its oxidized form as compared to the control. Thiram administration caused an increase in the activity of glutathione-dependent enzymes (glutathione peroxidase, glutathione transferase, and glutathione reductase). However, the time-course of enzyme activation in the gum tissues and oral fluid varied in dependence on the time of exposure to thiram. In the oral fluid of thiram-treated rats changes in the antioxidant glutathione system appeared earlier. The standard diet did not allow the glutathione pool to be fully restored to physiological levels after cessation of thiram intake. The use of exogenous antioxidants resviratrol and an Echinacea purpurea extract led to the restoration of redox homeostasis in the oral cavity.

While artificial intelligence drives remarkable progress in natural sciences, its broader societal implications are mostly disregarded. In this study, we evaluate environmental impacts of deep learning in materials science through extensive benchmarking. In particular, a set of diverse neural networks is trained for a given supervised learning task to assess greenhouse gas (GHG) emissions during training and inference phases. A chronological perspective showed diminishing returns, manifesting themselves as a 28% decrease in mean absolute error and nearly a 15,000% increase in the carbon footprint of model training in 2016-2022. By means of up-to-date graphics processing units, it is possible to partially offset the immense growth of GHG emissions. Nonetheless, the practice of employing energy-efficient hardware is overlooked by the materials informatics community, as follows from a literature analysis in the field. On the basis of our findings, we encourage researchers to report GHG emissions together with standard performance metrics., Competing Interests: The authors declare no competing interests., (© 2024 The Author(s).)

Reticular materials, including metal-organic frameworks and covalent organic frameworks, combine the relative ease of synthesis and an impressive range of applications in various fields from gas storage to biomedicine. Diverse properties arise from the variation of building units─metal centers and organic linkers─in almost infinite chemical space. Such variation substantially complicates the experimental design and promotes the use of computational methods. In particular, the most successful artificial intelligence algorithms for predicting the properties of reticular materials are atomic-level graph neural networks, which optionally incorporate domain knowledge. Nonetheless, the data-driven inverse design involving these models suffers from the incorporation of irrelevant and redundant features such as a full atomistic graph and network topology. In this study, we propose a new way of representing materials, aiming to overcome the limitations of existing methods; the message passing is performed on a coarse-grained crystal graph that comprises molecular building units. To highlight the merits of our approach, we assessed the predictive performance and energy efficiency of neural networks built on different materials representations, including composition-based and crystal-structure-aware models. Coarse-grained crystal graph neural networks showed decent accuracy at low computational costs, making them a valuable alternative to omnipresent atomic-level algorithms. Moreover, the presented models can be successfully integrated into an inverse materials design pipeline as estimators of the objective function. Overall, the coarse-grained crystal graph framework is aimed at challenging the prevailing atom-centric perspective on reticular materials design.