Modified simplified algorithm of the method of group consideration of arguments in simulation processes

There are many types and methods of simulation, but among them special attention should be paid to methods based on the theory of heuristic self-organization. All algorithms of the method of group argumentation (MGVA) are characterized by structural commonality on the principle of self-organization, which require insignificant requirements for a priori information to search for an infinite number of options. The advantage of the algorithm of the method of group consideration of arguments in comparison with other algorithms of this class is the presence of possibilities of expansion of the vector of initial data and the device for elimination of collinearity - reception of orthogonalization. MGVA consists of two blocks: pre-processing of observations taking into account the system of selected reference functions and calculation of selection applicants. As a result of the algorithm, models capable of controlling the process taking into account the phenomena accompanying a certain process are obtained. Given the commonality of the main provisions of the theory of self-organization of artificial neural networks and MGVA, the network variables are added to the model as a variable Z. As a result, we obtain a neural network that describes the physical phenomena accompanying the process. This will significantly increase the efficiency and accuracy of process management.

Planning of technical objects and systems

There are many types and methods of simulation, but among them special attention should be paid to methods based on the theory of heuristic self - organization. All algorithms of the method of group argumentation (MGVA) are characterized by structural commonality on the principle of self - organization, which require insignificant requirements for a priori information to search for an infinite number of options. The advantage of the algorithm of the method of group consideration of arguments in comparison with other algorithms of this class is the presence of possibilities of expansion of the vector of initial data and the device for elimination of collinearity - reception of orthogonalization. MGVA consists of two blocks: pre - processing of observations taking into account the system of selected reference functions and calculation of selection applicants. As a result of the algorithm, models capable of controlling the process taking into account the phenomena accompanying a certain process are obtained. Given the commonality of the main provisions of the theory of self - organization of artificial neural networks and MGVA, the network variables are added to the model as a variable Z. As a result, we obtain a neural network that describes the physical phenomena accompanying the process. This will significantly increase the efficiency and accuracy of process management.

Cyclohumulanoid Sesquiterpenes from the Culture Broth of the Basidiomycetous Fungus Daedaleopsis tricolor

A series of cyclohumulanoids, i.e., tricocerapicanols A–C (1a–1c), tricoprotoilludenes A (2a) and B (3), tricosterpurol (4), and tricoilludins A–C (5–7) were isolated along with known violascensol (2b) and omphadiol (8) from the culture broth of Daedaleopsis tricolor, an inedible but not toxic mushroom. The structures were fully elucidated on the basis of NMR spectroscopic analysis, and the suggested relative structures were confirmed via density functional theory (DFT)-based chemical shift calculations involving a DP4 probability analysis. In the present study, the 1H chemical shifts were more informative than the 13C chemical shifts to distinguish the diastereomers at C-11. The absolute configurations of 1–5 were determined by comparing the experimental and calculated electronic circular dichroism (ECD) spectra. For 6 and 7, the same chirality was assigned according to their biosynthetic similarities with the other compounds. The successful assignment of some Cotton effects was achieved by utilizing DFT calculations using simple model compounds. The plausible biosynthesis of 1–7 was also discussed on the basis of the structural commonality and general cyclohumulanoid biosynthesis. Compounds 2a and 5 were found to simultaneously induce hyphal swelling and branching at 5.0 μg/mL against a test fungus Cochliobolus miyabeanus.

Anti-CRISPR RNAs: designing universal riboregulators with deep learning of Csy4-mediated RNA processing

RNA-based regulation offers a promising alternative of protein-based transcriptional networks. However, designing synthetic riboregulators with desirable functionalities using arbitrary sequences remains challenging, due in part to insufficient exploration of RNA sequence-to-function landscapes. Here we report that CRISPR-Csy4 mediates a nearly all-or-none processing of precursor CRISPR RNAs (pre-crRNAs), by profiling Csy4 binding sites flanked by > 1 million random sequences. This represents an ideal sequence-to-function space for universal riboregulator designs. Lacking discernible sequence-structural commonality among processable pre-crRNAs, we trained a neural network for accurate classification (f1-score ≈ 0.93). Inspired by exhaustive probing of palindromic flanking sequences, we designed anti-CRISPR RNAs (acrRNAs) that suppress processing of pre-crRNAs via stem stacking. We validated machine-learning-guided designs with >30 functional pairs of acrRNAs and pre-crRNAs to achieve switch-like properties. This opens a wide range of plug-and-play applications tailored through pre-crRNA designs, and represents a programmable alternative to protein-based anti-CRISPRs.