Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system. Graphical Abstract

PROBLEM OF COMPUTER MODELING OF STEAM GENERATORS CHP-1 OF THE KORYAZHMA BRANCH OF ILIM GROUP AND WAYS OF SOLUTION

The concept of synthesis of a computer simulator model of a group of steam generators BKZ-160-100F is considered. An approach is formulated for constructing a mathematical de-scription structure with the possibility of parallelization of computational procedures

Methodology of Teaching Methods of FEM Analysis Using Software ANSYS

This paper presents the authors' experience of teaching the finite element method (FEM) at university. With the development of computational tools in the second half of the twentieth century, there was also the development of computational methods focused on the algorithmization of engineering tasks based on FEM. From the solution of individual problems of the state of stress and deformation from the influence of the external environment, a complex solution of the mutual interaction of the system of deformable bodies (elements) has been performed while improving the physical and geometric characteristics of modern materials and structures. Many processes in the automatic design system take place as if in a "black box" and the process of verifying the achieved results becomes the most important stage in the design activity. Without knowledge of the theoretical basis of FEM, physical and mathematical modeling, verification procedures and methods, the design of a structure cannot be safe and reliable. In this paper we present one of the possibilities how the student can get acquainted with the theoretical foundations of FEM and with computational procedures using ANSYS software.

Innovative Construction of the AFPM-Type Electric Machine and the Method for Estimation of Its Performance Parameters on the Basis of the Induction Voltage Shape

The article presents an innovative construction of the Axial Flux Permanent Magnet (AFPM) machine designed for generator performance, which provides the shape of induced voltage that enables estimation of the speed and rotational angle of the machine rotor. Design solutions were proposed, the aim of which is to limit energy losses as a result of the occurrence of eddy currents. The method of direct estimation of the value of the rotational speed and rotational angle of the machine rotor was proposed and investigated on the basis of the measurements of induced voltages and machine phase currents. The advantage of the machine is the utilization of simple and easy-to-use computational procedures. The acquired results were compared with the results obtained for estimation performed by using the Unscented Kalman Filter (UKF).

The Evaluation of Electric Power by Separate Analysis of Fourier Transform Components

This paper presents a substantiation of an approach for the evaluation of components of apparent power and intended to simplify the computational procedures which usually should be implemented in order to process the preliminary sampled waveform of instantaneous power. The results of carried out studies have shown that both active and reactive power can be calculated by the analysis of calculated components of sine and cosine Fourier transforms. This paper also presents the discussion of restrictions, which should be imposed on the duration of the analyzed signal and on frequencies of the auxiliary trigonometric functions, which are applied in order to calculate components of Fourier transform which are used for the evaluation of active and reactive power. The compliance with these restrictions allows us to eliminate the undesirable bias of active and reactive power estimation caused by the refusal from the decomposition of the analyzed waveform of the instantaneous power by applying the complete system of orthogonal trigonometric functions, as the evaluation of components of the apparent power is attained based on separate analysis of sine and cosine Fourier transforms calculated for the analyzed signal. The results of carried out simulations illustrate the frequency dependencies of sine Fourier transform calculated for the case of compliance with the restrictions, which allow to attain the highest accuracy of estimation and for the case when the duration of analyzed signal does not fit these restrictions.

Social Network Analysis: Towards Complexity Problem

Social network analysis is a advances from field of social networks. The structuring of social actors, with data models and involving intelligence abstracted in mathematics, and without analysis it will not present the function of social networks. However, graph theory inherits process and computational procedures for social network analysis, and it proves that social network analysis is mathematical and computational dependent on the degree of nodes in the graph or the degree of social actors in social networks. Of course, the process of acquiring social networks bequeathed the same complexity toward the social network analysis, where the approach has used the social network extraction and formulated its consequences in computing.

Higher Derivatives and Polynomials of the Standard Nield-Kuznetsov Function of the First Kind

In this fundamental work, higher derivatives of the standard Nield-Kuznetsov function of the first kind, and the polynomials arising from this function and Airy’s functions, are derived and discussed. This work provides background theoretical material and computational procedures for the arising polynomials and the higher derivatives of the recently introduced Nield-Kuznetsov function, which has filled a gap that existed in the literature since the nineteenth century. The ease by which the inhomogeneous Airy’s equation can now be solved is an advantage offered by the Nield-Kuznetsov functions. The current analysis might prove to be invaluable in the study of inhomogeneous Schrodinger, Tricomi, and Spark ordinary differential equations.

English Approximant Consonants: Pronunciation Difficulties Encountered by EFL Students

This research applied quantitative research. Quantitative is basically framed in term of using numbers, closed-end question. Quantitative research is characterized as an efficient examination of wonders by gathering quantifiable information and performing factual, scientific, or computational procedures. In collecting data, the researcher used pronunciation test as instrument in order to get the data. The items of pronunciation test consisted of a list of 120 words. Each sound consisted of 5 words. Pronunciation test was given to the respondents through asking them to pronounce the words clearly and correctly while the researcher was recorded. The result of the research data showed that the students made 1085 or 93.53% errors of substitution, 38 or 3.28% errors of omission, and 37 or 3.19% errors of addition from the total errors found. It indicated that most of the students made errors in substitution with high percentage than omission and errors of substitution had higher percentage than omission and addition. The result of the data analysis showed that there were 179 or 97.28% errors of substitution, 5 or 2.72% errors of omission, and there were no errors of addition found in pronouncing English approximant consonants. So, from all kinds of errors, most of the students made errors in substitution both fricative and approximant consonants.

Interval-Valued Hesitant Fuzzy Linguistic Multiattribute Decision-Making Method Based on Three-Parameter Heronian Mean Operators

Numerous variants have been proposed for sets of linguistic terms and the interval-valued hesitant fuzzy set (IVHFS). In particular, the interval-valued hesitant fuzzy linguistic set (IVHFLS) is more suitable for defining the hesitancy and inconsistency inherent in the human cognitive processes of decision making. A key aggregation operator is Heronian mean (HM), based on which the correlation among aggregated arguments can be captured. However, the existing HM operators partially overlook the correlation among more than two arguments and lack the properties of idempotency and reducibility. In this work, the limitations of HM operators are first analyzed. Then, two new HM variants are introduced: three-parameter weighted Heronian mean (TPWHM) and three-parameter weighted geometric Heronian mean (TPWGHM). Thus, the reducibility, idempotency, monotonicity, and boundedness properties are proven for the two computational procedures, and unique situations are mentioned. Furthermore, two more elaborate operators are also introduced which are called the interval-valued hesitant fuzzy linguistic TPWHM (IVHFLTPWHM) and the interval-valued hesitant fuzzy linguistic TPWGHM (IVHFLTPWGHM). The main properties, as well as unique situations of these two computational procedures, are discussed. Finally, the introduced methods are clarified by illustrative examples. In addition, the parameter effects on the decision-making outcomes are discussed and comparisons with other reference methods are made.

Genomic approaches to trace the history of human brain evolution with an emerging opportunity for transposon profiling of ancient humans

Transposable elements (TEs) significantly contribute to shaping the diversity of the human genome, and lines of evidence suggest TEs as one of driving forces of human brain evolution. Existing computational approaches, including cross-species comparative genomics and population genetic modeling, can be adapted for the study of the role of TEs in evolution. In particular, diverse ancient and archaic human genome sequences are increasingly available, allowing reconstruction of past human migration events and holding the promise of identifying and tracking TEs among other evolutionarily important genetic variants at an unprecedented spatiotemporal resolution. However, highly degraded short DNA templates and other unique challenges presented by ancient human DNA call for major changes in current experimental and computational procedures to enable the identification of evolutionarily important TEs. Ancient human genomes are valuable resources for investigating TEs in the evolutionary context, and efforts to explore ancient human genomes will potentially provide a novel perspective on the genetic mechanism of human brain evolution and inspire a variety of technological and methodological advances. In this review, we summarize computational and experimental approaches that can be adapted to identify and validate evolutionarily important TEs, especially for human brain evolution. We also highlight strategies that leverage ancient genomic data and discuss unique challenges in ancient transposon genomics.