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Application of machine learning algorithms in drug screening
Get PDFAt present, in the medical field, drug screening is usually performed using in vivo drug experiments. However, it is very time-consuming and laborious to conduct in vivo experiments on a large number of drugs to be screened one by one. This paper attempts to propose using machine learning algorithms to perform preliminary screening of a large number of compounds to be screened and their molecular structures to reduce the workload of in vivo experiments. Among them, it is internationally recognized that there is an important association between breast cancer progression and the alpha subtype of the estrogen receptor. Anti-breast cancer drug candidates with excellent efficacy need to contain compounds that can better antagonize ERα activity. In this paper, the research object is narrowed down from compounds to the molecular structure of the compounds, and then the random forest regression algorithm is used to develop the molecular structure-ERα activity prediction model. Molecular structures with significant effects on biological activity were screened from molecular structure descriptors in numerous compounds. Four different kernel functions were used to conduct comparative experiments, and finally a support vector regression algorithm based on radial basis kernel function was established, which realized the quantitative prediction of compounds on biological activity of ERα, and could find potential compounds beneficial to breast cancer treatment. This is a novel, computer-based method for preliminary drug screening, which can help medical researchers effectively narrow the scope of experiments and achieve more accurate optimization of drugs
Analysis of methods for improving the efficiency of “Iceberg” gas air coolers
Get PDFRussia has the largest volume of natural gas reserves in the world. Recoverable natural gas reserves amount to about 67 trillion cubic meters, according to the Ministry of Natural Resources and Environment of the Russian Federation for 2023. In recent years, the development of the Unified Gas Supply System has been growing rapidly. Since 2021 the Government of the Russian Federation has been actively introducing draft laws and regulations related to the scaling of the country’s gasification. In June 2021 came out the Federal Law No. 184-FZ, which instructed the Government of the Russian Federation to adopt regulations aimed at implementation of provisions of free gasification of the country [1]. In September 2021 there was issued Decree No. 1547, [2] approving the new Rules for connecting gas-using equipment and capital construction facilities to gas distribution networks, which introduces the concept of pre-gasification. It is worth noting that new gas mains, compressor stations (CS) are put into operation, active reconstruction of the existing shops with exhausted gas compressor units (GCU) is carried out. One of the most urgent issues of the gas industry today is the efficient use of energy resources. Besides using the energy of flue gases from gas turbine drive of GPA, energy at gas throttling at gas distribution stations and other methods of energy saving, the significant role is played by the effective operation of air coolers of gas (ACG), the operation of which affects the reliable transportation of gas in the main gas pipeline (MG). The paper analyzes the methods of technical condition of gas air cooling devices of “Iceberg” type operated at the production site of the booster compressor station of “Gazprom Dobycha Nadym” LLC. The thermal efficiency of air coolers with all fans turned on and off was determined for the coldest and hottest months of the year. The electric energy savings of the frequency controlled drive (VFD) were calculated
Optimizing and reliability analysis by firefly and genetic algorithms for a quadcopter
Get PDFOur study aims to obtain the highest level of reliability for a quadcopter, taking financial and mass limitations into account, to achieve the highest level of reliability with the lowest mass and cost. For this purpose, we first calculated the reliability and the relationships that govern it, and based on these relationships, we determined the reliability of the quadcopter subsystems. In order to achieve the highest level of reliability, we utilized optimization algorithms. It is possible to increase the reliability of a system through several methods, such as enhancing the quality of parts and components, using surplus components, improving the quality of parts and components by always using surplus components, and redesigning the system. This study examines the possibility of increasing quadcopter reliability by using additional parts and optimizing it using the firefly algorithm. Lastly, in order to validate the results obtained from the firefly algorithm, we implemented the problem once again using the genetic algorithm and compared the results obtained from both algorithms. After 20 times of running the algorithms, the optimal reliability values were 0.99925 for the firefly algorithm and 0.99999 for the genetic algorithm
Capillary force method to improve the green density of binder jet additive manufacturing
Get PDFThis study investigates the impact of capillary adhesion force on the green part density in metal powder binder jetting 3D printing. Gas atomized Co-Cr-Mo, SS316L, and pure Cu powders were used to print various samples. The printed samples were then treated with water, 1-Hexanol, and n-Amyl alcohol vapor for 24 hours to nucleate capillary bridges between particles and shrink samples uniformly. The volume change was calculated for each sample, and up to –3.1 % volume change was observed. The proposed method can be used to improve green part densities directly on printed parts before sintering
Decarbonisation options of existing thermal power plant burning natural gas
Get PDFNowadays power industry faces deepest crises ever with unprecedented prices shocks and climate challenges at the same time. From one hand we realise the need of energy transformation of power industry towards more sustainable future with climate neutral technologies. From the other hand it become obvious that this change could not happen immediately and transition period is needed with some fossil fuel technology still playing an important role as a back-up for renewable energy sources. The biggest question what is the best and cost-efficient way to decarbonise existing thermal power generation. We try to address it on the example of existing combined cycle gas turbine (CCGT) power plant fuelled by natural gas. Clearly the following possible options were identified: 1) replacement of natural gas with alternative gases, such as green hydrogen, bio or synthetic methane, 2) carbon capture and underground storage (CCS) in geological formations, 3) carbon capture, liquefaction and export, 4) carbon capture and utilisation (CCU). US giant General Electric in its publication “Decarbonizing gas turbines through carbon capture” is considering similar options for decarbonising of gas turbines. They divide it into two approaches: 1) pre-combustion by using a zero or carbon neutral fuels, such as hydrogen, synthetic methane, biofuels or ammonia and 2) post-combustion by removing carbon from the plant exhaust, using liquid or solid sorbents or oxy-fuel cycles. In this publication we try to compare these different options, despite they are not clearly comparable. For the analysis we take natural gas fired CCGT plant Riga TPP-2 in Latvia with installed capacity of 881 MW (in condensing mode)
Dynamic response of a space flexible arm with a moving mass
Get PDFThe dynamic characteristic of a space rotating flexible arm with moving mass were investigated. The space arm with moving mass can rotate around the fixed end in horizontal and vertical planes simultaneously. And the lateral deflections of the arm in the two planes were considered. The equations of the structure were derived by the Lagrange’s equation with the assumed mode method. And a system of binary second order linear differential equations is gotten. Based on the central difference method, a conditionally stable algorithm for solving the equations is established. Due to the coupling of lateral displacements of the arm in horizontal and vertical planes, the increase of the angular velocity in one plane will increase the lateral displacements in the other plane. When the angle between the arm and the horizontal plane increases, the component of gravity along the normal direction of the beam will decrease, resulting in a decrease in lateral displacements in vertical plane, however, it will lead to a decrease in stiffness in horizontal plane and thus an increase in lateral displacements. Compared with moving mass, moving load ignores the influence of inertial force, so the calculation results of moving mass and moving load are different. The conclusions provide calculation basis for the design of similar structures
Test case simplification based on coupling metrics in software bug location
Get PDFSoftware test cases are one of the most critical aspects of software testing in the product development process. As software products are updated several times, the same test requirement may be covered by multiple test cases, so this aspect is often redundant, yet the approximate test case set has an impact on its error detection rate. This study proposes the idea of using redundant test cases in software error location, introduces a coupling metric, analyses its program slicing and establishes a second coverage criterion in order to balance the relationship between the reduced test suite and the false detection rate the test case set. The results show that the size of test set and the number of error detection by the Ruby On Rails (ROR) method used in this study are larger than those of other commonly used reduction algorithms. The test suite has the lowest error detection loss rate, with an average of 17.96 % across the six test case sets. The highest error detection capability of individual test cases was found in the reduced test set, with a mean value of 90.63 % in the test set. The method also has the highest average reduction efficiency of 91.05 %. Compared with other simplification methods, the research method has a better balance between the size and false detection rate of the reduced test suite and the advantages of simplification
Super resolution direction finding technique of vortex electromagnetic wave radar in missing mode
Get PDFVortex electromagnetic waves have superior performance over electromagnetic waves. In order to improve the radar super-resolution lateralization technique in its missing modes, this study proposes to start from the perspective of mode missing. The missing modes are reconstructed using the Adaptive Step Size Gradient Descent (ASSGD) method by exploiting the features of the missing modes. The linear minimum mean square error (LMMSE) estimation method is also used to solve the problem of poor reconstruction accuracy due to the Missing Modes. The Missing Modes Iterative Adaptive Approach (MMIAA) algorithm and Missing Modes Sparse Learning via Iterative Minimization (MMSLIM) algorithm are then used. Minimization (MMSLIM) algorithm to recover missing modes. The results showed that the RMSEs of the recovery errors of MMSLIM, MMIAA and ASSGD were 0.16, 0.31 and 0.82 respectively at a modal missing ratio of 0.7, while ASSGD fails to recover the missing modal data at a modal missing ratio of 0.9. The overall data quality of the azimuthally estimated RMSE was average when the signal-to-noise ratio was at [–5, 10] dB. And the curve becomes flatter when it reaches 15 dB or more, indicating that MMSLIM, MMIAA has important theoretical and practical value
Neural solution of elliptic partial differential equation problem for single phase flow in porous media
Get PDFPartial differential equations are used to model fluid flow in porous media. Neural networks can act as equation solution approximators by basing their forecasts on training samples of permeability maps and their corresponding two-point flux approximation solutions. This paper illustrates how convolutional neural networks of various architecture, depth and parameter configurations manage to forecast solutions of the Darcy’s flow equation for various domain sizes
Modern biophysical view of electromagnetic processes of the phenomenon of life of living biological systems as a promising basis for the development of complex medicine: the role of biophotons
Get PDFThe results of a theoretical study of the role of biophotons in electromagnetic process of realizing the phenomenon of life are presented in the article. This article is a continuation of the theoretical study of the team of authors, which was published in the Journal of Complexity in Health Sciences, Vol. 5, Issue 1, 2022, p. 22-34 and Vol. 5, Issue 2, 2022, p. 45-57. The aim of the theoretical study was to generalize the available scientific physical and biological knowledge of modern science about the role of biophotons in the electromagnetic processes of the phenomenon of life at the cellular level in order to deepen the fundamental knowledge of Complex Medicine. This study is a fragment of research work on “Development of algorithms and technologies for implementing a Healthy Lifestyle in patients with Noncommunicable Diseases based on the study of functional status” (state registration number 0121U108237: UDC 613 616-056-06: 616.1/9-03). General scientific methods and theoretical methods were used in this theoretical study. Based on the results of this fragment of the theoretical study, twelve conclusions were formulated. The formulated conclusions conceptualize such basic questions as: all living cells at the nanoscale consist of electromagnetic fields and generate electromagnetic fields, cell signaling and all cellular processes are due to electromagnetic interactions, ultra-weak photon emission is a universal optical phenomenon for all cells and plays an important role in communication and in cell life throughout the body