Numerical Computer Model Research Articles

Dam-Break Waves’ Hydrodynamics on Composite Bathymetry

Among others, dam-break waves are a common representation for tsunami waves near- or on-shore as well as for large storm waves riding on top of storm surge water levels at coasts. These extreme hydrodynamic events are a frequent cause of destruction and losses along coastlines worldwide. Within this study, dam-break waves are propagated over a composite bathymetry, consisting of a linear slope and an adjacent horizontal plane. The wave propagation on the slope as well as its subsequent inundation of the horizontal hinterland is investigated, by varying an extensive set of parameters, for the first time. To that end, a numerical multi-phase computational fluid dynamics model is calibrated against large-scale physical flume tests. The model is used to systematically alter the parameters governing the hydrodynamics and to link them with the physical processes observed. The parameters governing the flow are the slope length, the height of the horizontal plane with respect to the ocean bottom elevation, and the initial impoundment depth of the dam-break. It is found that the overland flow features are governed by the non-dimensional height of the horizontal plane. Empirical equations are presented to predict the features of the overland flow, such as flow depth and velocities along the horizontal plane, as a function of the aforementioned parameters. In addition, analytical considerations concerning these dam-break flow features are presented, highlighting the changing hydrodynamics over space and time and rising attention to this phenomenon to be considered in future experimental tests.

The Impact of a Complex Computer Numerical Model Based on Economic Cooperation on the Value Chain of International Trade Facilitation

With the advancement of global economic integration, traditional trade barriers have been greatly reduced, and the marginal utility of tariff reductions on trade expansion has become weaker and weaker. Especially under the global value chain division of labor system, intermediate products and parts have undergone multiple cross-border trades. The cumbersome trade procedures will greatly increase trade costs and destroy the driving force of trade. After improving infrastructure and optimizing customs clearance procedures, with the improvement of convenience, more countries and enterprises can participate in the global division of labor. Considering the industry characteristics of high-tech manufacturing, this paper selects panel data of high-tech manufacturing from multiple sample countries and uses the panel data two-way fixed-effect model to empirically analyze the impact of a country’s trade facilitation level on the global value chain of high-tech manufacturing in a country. From the perspective of global value chain status, the improvement of a country’s level of trade facilitation can significantly promote the country’s high-tech manufacturing global value chain status. The level of foreign direct investment, the degree of opening to the outside world, the level of government public services, the level of human capital, and the R&D capability are all significantly positive at the 1% level, while the level of physical capital is significantly negative at the 1% level.

Temperature distribution analysis of carbon fiber reinforced polymer composites during self-resistance electric heating process

Self-resistance electric (SRE) heating for carbon fiber reinforced plastics (CFRP) is an alternative out-of-autoclave curing methodology that has high efficiency and low energy consumption. However, thanks to the heating mechanism of inside-out conduction, which is significantly different from that of the traditional outside-in heating process, the temperature distribution and its homogenization strategy still need further investigation. This work focuses on analyzing the affecting factors of the temperature uniformity of CFRP laminates during the SRE curing process utilizing a multi-physical numerical computation model and experimental verification. It is found that mold sizes have the most significant impact due to the non-uniform center-to-edge heat absorption of the mold. The maximum temperature difference during the untreated process could be lower than 20 K if the excess size proportion of the mold is smaller than 10%. Thermal barriers made of aerogel homogenize the temperature distribution during the dwell stage, reducing the maximum temperature difference by 84.18%. Considering that the mold size is sometimes unchangeable, the existence of auxiliary heating elements compensates the heat dissipation from the self-heated laminate and reduces the maximum temperature difference by 79.81%. Based on analysis results, a temperature homogenization strategy is proposed, where the maximum temperature difference is reduced by 86.15%.

Multi-Task Learning for Concurrent Prediction of Thermal Comfort, Sensation and Preference in Winters

Indoor thermal comfort immensely impacts the health and performance of occupants. Therefore, researchers and engineers have proposed numerous computational models to estimate thermal comfort (TC). Given the impetus toward energy efficiency, the current focus is on data-driven TC prediction solutions that leverage state-of-the-art machine learning (ML) algorithms. However, an occupant’s perception of indoor thermal comfort (TC) is subjective and multi-dimensional. Different aspects of TC are represented by various standard metrics/scales viz., thermal sensation (TSV), thermal comfort (TCV), and thermal preference (TPV). The current ML-based TC prediction solutions adopt the Single-task Learning approach, i.e., one prediction model per metric. Consequently, solutions often focus on only one TC metric. Moreover, when several metrics are considered, multiple ML models for a single indoor space lead to conflicting predictions, rendering real-world deployment infeasible. This work addresses these problems by leveraging Multi-task Learning for TC prediction in naturally ventilated buildings. First, a survey-and-measurement study is conducted in the composite climatic region of north India, in 14 naturally ventilated classrooms of 5 schools, involving 512 primary school students. Next, the dataset is analyzed for important environmental, physiological, and psycho-social factors that influence thermal comfort of children. Further, “DeepComfort”, a deep neural network based Multi-task Learning model is proposed. DeepComfort predicts multiple TC output metrics viz., TSV, TPV, and TCV, simultaneously through a single model. It is validated on ASHRAE-II database and the primary student dataset created in this study. It demonstrates high F1-scores, Accuracy (≈90%), and generalization capability, despite the challenges of illogical responses and data imbalance. DeepComfort is also shown to outperform 6 popular metric-specific single-task machine learning algorithms.

A review of computational models for underwater acoustic radiation induced by structural vibration in the shallowmarine environment

<p indent="0mm">The vibration and acoustic performance of underwater structures have always been a research hotspot in the field of ocean engineering. The acoustic stealth technology of submarines and the marine hydroacoustic detection technology are based on the accurate prediction and effective control of the underwater structural vibration and acoustic behavior in the marine environment. For vibration and acoustic analysis in the marine environment, most of the early studies regarded the marine environment as an infinite fluid region, or a semi-infinite fluid region with a free sea surface. These two marine models simplify the simulation process of underwater acoustic radiation and propagation by ignoring the impact of the seabed. Underwater acoustic radiation and propagation caused by structural vibrations in the shallow marine environment will be greatly affected by the reflection and refraction effects at the sea surface and seabed. Moreover, the sound velocity in the shallow marine environment usually shows different profiles due to the influences of the water pressure and temperature, which affects the vibration and acoustic behavior of underwater structures. To accurately characterize the coupling effect of underwater structures and shallow marine environments, many researchers have devoted their particular efforts to the analysis of vibration and acoustic radiation of underwater structures in the shallow marine environment, and have developed a variety of numerical computational models, such as the finite element method, finite element-boundary element method, finite element-wave superposition method, finite element-singular boundary method, finite element-parabolic equation method and finite element-normal mode method, and so on. This paper focuses on deterministic computational models for vibration and acoustic analysis of underwater structures in the mid-low frequency range, and discusses two analytical schemes: Wet modal analysis and dry modal analysis. The development and application status of the computational models for the vibration and acoustics of underwater structures in the shallow marine environment are reviewed from the aspects of underwater acoustic models and numerical algorithms. Among those computational models, the finite element method combined with absorbing boundary layers is a common and efficient computational model, which is suitable for the analysis of near-field acoustic radiation induced by structural vibrations in the shallow marine environment. By contrast, the boundary discretization schemes, such as the boundary element method, wave superposition method and singular boundary method, avoid the special truncated treatment of marine domains by using the Green’s function derived from the mirror virtual source method and the normal mode model. Therefore, the hybrid computational solvers, such as the finite element-boundary element method, finite element-wave superposition method and finite element-singular boundary method, can be applied to the analysis of vibration and acoustic behaviors of the near- and far-field vibration and acoustic analysis. On the other hand, based on the wet modal analysis, the finite element-wave superposition method, finite element-parabolic equation method and finite element-normal mode method have higher computational efficiency in far-field acoustic propagation problems induced by vibration of underwater structures. Finally, the future development and application prospect of computational models for vibration and acoustic analysis of underwater structures in the shallow marine environment are discussed. Most of the existing computational models are based on the shallow marine environment of the horizontal sea surface and seabed. In future development, it is necessary to broaden the application scope of computational models, improve the computational efficiency of numerical algorithms, introduce the efficient optimization algorithm to develop a high-performance computational model for the optimal design of vibration and noise reduction of underwater structures in the typical and complex shallow marine environment.

Prediction of environment pollution by employing long short-term memory network

Air pollution levels have risen as an outcome of urban and industrial development in so many developing countries. People and governments all around the world are concerned about air pollution, which has a severe influence on both personal health and long-term global development. As a government, it is responsible for preventing and controlling air pollution, as well as monitoring the pollutant's impacts on human health. There are numerous computer models available, ranging from statistics to artificial intelligence. Pollution levels are still out of control in some parts of the world due to a wide range of sources and factors. Because of accurate estimates of future air pollution, the government can take necessary action. Forecasting air pollution levels based on environmental data is becoming increasingly relevant as people become more worried about global warming and urban sustainability. For replicating the complicated linkages between these variables, advanced Deep Learning (DL) algorithms hold enormous promise. The objective of this work is to provide a high level of accurate solution to the air pollution forecasting problem. Kaggle data will be employed to train a DL model that will forecast air pollution levels.

Factors affecting the cathode/electrolyte interfacial pH change during water reduction: A simulation study

Water reduction reaction to produce hydrogen has been extensively studied in electrochemical and photoelectrochemical water splitting. The cathode/electrolyte interfacial pH change (ΔpH) during water reduction has a non-negligible impact on the activity and stability. However, there are difficulties in experimentally detecting pH change of the localized solution close to the electrode. Herein, a one-dimensional finite element numerical computational model is proposed to simulate the water reduction process. Potential, bulk pH, temperature, and buffer species are considered as variable factors to investigate their effects on interfacial pH change. The interfacial ΔpH could decrease to a large extent as the bulk pH increases. The ΔpH in the whole diffusion layer would decrease when buffer species is introduced. Whereas, the impact of temperature is less significant. According to the simulation results, raising the bulk pH and introducing buffer species can keep the interfacial pH change within 1 unit, which is an efficient route to stabilize water electrolysis.

Computation of the Electrical Resistance of a Low Current Multi-Spot Contact.

In high complexity electrical systems such as those used in the automotive industries, electric connectors play an important role. The automotive industry is gradually shifting its attention to electric cars, which means more electrical connectors for sensors and data collection. A fault in connectors for sensors used in a vehicle can cause drastic damage to capital equipment and, in the worst case, the loss of life. The studies of faults or degradation of electrical contacts are essential for safety in vehicles and various industries. Although such faults can be due to numerous factors (such as dust, humidity, mechanical vibration, etc.) and some yet to be discovered, high contact resistance is the main factor causing erratic behavior of electrical contacts. This paper presents a study on the computation of electrical contact resistance of two metal conductors (in the form of a disk) with analytical relations and a numerical computation model based on the finite element method (FEM) in COMSOL Multiphysics. The contact spots were considered to have a higher electrical resistivity value (ρcs) than those of the two metal conductors (ρCu). Studies such as the one in view that is carried out on a microscopic level are often difficult to investigate experimentally. Therefore, with the help of a simplified numerical model, the consequences of the degradation of electrical contacts are investigated. To validate the FEM model, the numerical results were compared to those obtained from analytical models.

Study of Various Epoxy-Based Surface Coating Techniques for Anticorrosion Properties

Polyepoxides are a kind of chemical polymerization that is widely employed in several industrial purposes. Due to their macromolecular structure, polyepoxides offer superior superficial treatment and antierosion activity compared to basic organic corrosion inhibitors. During metal-inhibitor interactions, the polyepoxides outlying glacial efficient clusters operate as adsorption centers. Numerous polyepoxides have been employed as anticorrosive coating materials in both pure and cured forms, most notably for ferrite in acidic and NaOH solutions. The majority of polyepoxides operate as inhibitors of interface and mixed-type corrosion. Numerous computer models have been done to illustrate the anticorrosive properties of polyepoxides on metallic shells and their adsorption behavior. However, because the majority of polyepoxides have low solubility, they are best used as anticorrosive coating materials. Numerous polyepoxides-based coatings have been created and effectively applied on ferrite and aluminum in salt-water solution according to a review of the literature. Natural and synthetic additives can be used to further enhance the anticorrosive properties of polyepoxides coatings. This review article compiles published findings on the anticorrosive properties of pure and cured polyepoxides for a variety of metals and alloys in a variety of electrolytes.

Research on the use of silica aerogels

Silica aerogels are alternative thermal insulation materials for external wall structures. They have a minimum density and water resistance, which in a period of global warming and in a hot climate allows you to get the necessary protective shell of the building. High technologies contribute to a significant improvement in the quality of insulation through the use of aerogel structures. A promising direction in the field of research is to improve the technical characteristics of the insulation used and reduce the costs of its manufacturing process. The aim of the work was to conduct an experiment on a room model and evaluate the possibilities of using silica aerogels as a light thermal insulation material. Within the framework of the study, the tasks were solved using numerical computer modeling. The stages of obtaining aerogels with the specified parameters are reduced into a clear technological sequence, which allows us to justify their physical and thermal properties. Based on the experience of conducting research, the indicators of the use of aerogels in construction are analyzed. An experiment was conducted on a model of a room with aerogel insulation and the radiation from mutually located surfaces was determined. According to the results of the work, a predictable and regular decrease in temperature was obtained over time. Aerogel sheets turned out to be rational materials for walls and other elements of buildings, because along with low density, they have a high thermal insulation ability. The practical benefit of the study lies in the fact that the obtained dependencies allow us to recommend the use of aerogel insulation not only for load-bearing and enclosing structures, but also for individual elements of buildings and can be used to develop methods to increase thermal protection.

ANALYTICAL AND NUMERICAL COMPUTATION OF ELECTRICAL RESISTANCE IN A LOW CURRENT MULTI-SPOTS METALLIC CONTACT

The problem concerning the specific resistance of electrical contacts is still of special importance especially in high complexity electrical systems or critical operation devices such as those used in the automotive industry. A huge number of studies have been conducted over time in order to develop easy models that allow the calculation of the contact resistance at the interface between two conductors taking into account the discontinuity of the contact surface. This paper presents a study on the computation of the contact resistance of two metal conductors with analytical relations and, respectively, using numerical computation models. The aim of this paper is to examine the differences between the results obtained using analytical models and numerical model based on finite element method (FEM) in COMSOL Multiphysics.

The Influences of Local Glacitectonic Disturbance on Overconsolidated Clays for Upland Slope Stability Conditions: A Case Study

Reliability of equilibrium state evaluation about settlement slopes in the context of natural and human-made hazards is a complex issue. The geological structure of the vicinity of the upland slope in the urban environment of Warsaw is characterised by a significant spatial diversification of the layers. This is especially due to the glacitectonics in the Mio-Pliocene clays, which are located shallowly under the sandy tills’ formations. With substantial variability in the clay roof surface, point recognition by drilling is often insufficient. The use of electrical resistivity imaging (ERI) in the quasi-3D variant provides accurate images of the real ground conditions, which is crucial in optimal geotechnical design. In forecasting the behaviour of the slope, it is necessary to quantify the impact of spatially differentiated systems of disturbed layers on changes in the safety factor (SF), which corresponds to the observed landslide activity of the Warsaw Slope. This study concerns numerous calculation model analyses of the optional clay position in the context of slope stability conditions. A wide range of soil properties variability was taken into account, resulting from both lithogenesis and subsequent processes disintegrating the original soil structure. Regarding the geological conditions of the slip surface, the use of classical computational methods and numerical modelling (FEM) was considered for comparative purposes. The results indicated that local changes in equilibrium conditions were affected by the different morphology of the clay roof surface of the slope and the alternation in strength characteristics on the slip surfaces. The findings of the study contribute to sustainable spatial planning of near-slope regions.

Numerical manifold computational homogenization for hydro-dynamic analysis of discontinuous heterogeneous porous media

In this paper, a mixed two-scale numerical manifold computational homogenization model is presented for dynamic analysis and wave propagation of the discontinuous heterogeneous porous media based on the first-order homogenization theory. Instead of the conventional version which neglects microscopic dynamics, the extended Hill–Mandel lemma is employed to incorporate the microscale dynamic effects. Microscale and macroscale Initial Boundary Value Problems (IBVPs) are solved simultaneously using the Numerical Manifold Method (NMM) with the information conveyed between different scales. The microscale IBVP is solved under Linear Boundary Conditions (LBCs) and Periodic Boundary Conditions (PBCs) that are defined with macroscale solid displacement, fluid pressure and their first-order gradients. The discontinuous macroscale IBVP is solved iteratively using the Newton method with the macroscale internal forces and Jacobian determined by solving the microscale IBVPs. A stick–slip contact model is implemented using an augmented Lagrange multiplier method to impose frictional contact conditions along the macroscale discontinuities. Through various numerical simulations, the presented two-scale NMM is shown to be able to effectively and accurately capture the fully dynamic and wave propagation responses of the discontinuous heterogeneous porous media under the fluid injection and impact loading condition.

ICYP-MFE: Identifying Human Cytochrome P450 Inhibitors Using Multitask Learning and Molecular Fingerprint-Embedded Encoding.

The human cytochrome P450 (CYP) superfamily holds responsibilities for the metabolism of both endogenous and exogenous compounds such as drugs, cellular metabolites, and toxins. The inhibition exerted on the CYP enzymes is closely associated with adverse drug reactions encompassing metabolic failures and induced side effects. In modern drug discovery, identification of potential CYP inhibitors is, therefore, highly essential. Alongside experimental approaches, numerous computational models have been proposed to address this biochemical issue. In this study, we introduce iCYP-MFE, a computational framework for virtual screening on CYP inhibitors toward 1A2, 2C9, 2C19, 2D6, and 3A4 isoforms. iCYP-MFE contains a set of five robust, stable, and effective prediction models developed using multitask learning incorporated with molecular fingerprint-embedded features. The results show that multitask learning can remarkably leverage useful information from related tasks to promote global performance. Comparative analysis indicates that iCYP-MFE achieves three predominant tasks, one equivalent task, and one less effective task compared to state-of-the-art methods. The area under the receiver operating characteristic curve (AUC-ROC) and the area under the precision-recall curve (AUC-PR) were two decisive metrics used for model evaluation. The prediction task for CYP2D6-inhibition achieves the highest AUC-ROC value of 0.93 while the prediction task for CYP1A2-inhibition obtains the highest AUC-PR value of 0.92. The substructural analysis preliminarily explains the nature of the CYP-inhibitory activity of compounds. An online web server for iCYP-MFE with a user-friendly interface was also deployed to support scientific communities in identifying CYP inhibitors.

Теоретичне дослідження стійкості руху асиметричного гичкозбирального машинно-тракторного агрегату

Goal. To determine based on numerical computer modeling of the obtained analytical dependences the parameters of stable plane-parallel motion of an asymmetric top-gathering machine (TGM). Methods. Methods of higher mathematics for the transformation of systems of differential equations, the theory of stability of motion, automatic control, the study of the behavior of tracking systems, a compilation of computer programs, numerical calculations, construction of graphical dependencies and their analysis are used. Results. According to the results of the analytical study, the values are gained of the amplitude and phase-frequency characteristics of the oscillations of the course angle of the tractor during the reproduction of the perturbing unit in the form of oscillations of the angle of rotation of the hitch in the horizontal plane. Based on mathematical modeling data the necessary graphic dependences are constructed. Their analysis made it possible to establish the influence of the working speed of the test unit, the values of the input coefficients of the tires of the front and rear wheels of the tractor, as well as the layout of the power tool (universal or integrated) on the stability of the test unit. Conclusions. Based on the received system of differential equations the stability of movement of the asymmetric TGM during the performance of the technological process is investigated. Quantitative indicators of this stability are the values of the amplitude and phase-frequency characteristics of the oscillations of the course angle of the tractor during the development by the unit of external perturbation in the form of oscillations of the angle of rotation of the TGM. Calculations have shown that reducing the value of the input coefficient of the tires of the tractor wheels increases its sensitivity to the effects of perturbation. This sensitivity is greater the closer the wheels of the power tool are located to the point of attachment of the trailed TGM. From tractors of classical and integral arrangement at the assembly of the asymmetric TGM, the preference should be given to the first one. According to the results of mathematical modeling, the qualitative increase in the speed of the tractor based on tractors of both schemes from 1.5 to 2.5 m/s leads to an undesirable increase in amplitude-frequency response and the desired increase in phase-frequency response during their reproduction of external disturbance in the form of oscillations of the angle of rotation of the TGM. At the same time, in quantitative terms, the sensitivity of the unit based on a classic tractor to the effect of perturbing on the amplitude is 11–12% less, and the phase shift — almost the same, which is the best option in terms of stability of the tractor in the horizontal plane.

Coastal erosion assessment using remote sensing and computational numerical model. Case of study: Libertador Bolivar, Ecuador

The sea-level rise has intensified the erosion of coastal zones, whereby the coastal management requires tools to evaluate and predict the dynamics of shoreline. In this paper we evaluate the impact of erosion in a coastal zone of the active margin of Ecuador, where the subduction causes vertical movements of coast. The area chosen to develop this study Playa Bruja and Libertador Bolivar beaches in which activities such as tourism, fisheries, agriculture and gastronomy are the main sources of income. This study analyzes the shoreline retreatment from 1986 to 2019, by using aerial images (remote sensing), along to selected beaches to validate a computational numerical model as MIKE Zero. This calibrated model permitted us to evaluate possible scenarios and hazards until 2025 (with or without coastal protection such as offshore breakwaters), to promote integrated coastal management for decision-makers, especially considering the possible collapse of one of the main coastal highways (E15) of Ecuador country. The result from remote sensing suggests a mean rate of erosion of 0.64 m/yr, which well-correlate with the outputs from the numerical model (between 0.4 and 0.7 m/yr). The net transport, influenced by waves, was calculated in 470m3/day (1.71 E+5 m3/yr), predominant to the north. These results allowed us to categorize three levels of erosion threat such as high (45%), medium (46%), and low (9%) and this classification allows to observe which areas are more exposed or have a higher threat and then propose alternatives to protect. Future scenarios under natural conditions show a continuous retreat of the coast that put in risk the community and hypothetic scenario under an arrangement of 5 breakwaters generates accretion next to Playa Bruja Beach but a deficient supply at the north side at Libertador Bolivar.

Organic and inorganic equivalent models for analysis of red blood cell mechanical behaviour

Experimental investigation into the mechanical response of red blood cells is presently impeded with the main impediments being the micro dimensions involved and ethical issues associated with in vivo testing. The widely employed alternative approach of computational modelling suffers from its own inherent limitations being reliant on precise constitutive and boundary information. Moreover, and somewhat critically, numerical computational models themselves are required to be validated by means of experimentation and hence suffer similar impediments. An alternative experimental approach is examined in this paper involving large-scale equivalent models manufactured principally from inorganic, and to lesser extent organic, materials. Although there presently exists no known method providing the means to investigate the mechanical response of red blood cells using scaled models simultaneously having different dimensions and materials, the present paper aims to develop a scaled framework based on the new finite-similitude theory that has appeared in the recent open literature. Computational models are employed to test the effectiveness of the proposed method, which in principle can provide experimental solution methods to a wide range of practical applications including the design of red-blood cell nanorobots and drug delivery systems. By means of experimentally validated numerical experiments under impact loading it is revealed that although exact prediction is not achieved good accuracy can nevertheless be obtained. Furthermore, it is demonstrated how the proposed approach for first time provides a means to relate models at different scales founded on different constitutive equations.

Computational modeling of a 3D matrix of duplex stainless steel and its ultimate strength in function of the sigma phase evolution

The appearance of intermetallic phases in steels is a matter of great interest due to the harmful character they can confer to the material's mechanical properties. This study presents the effect of the sigma phase's appearance for duplex stainless steel through numerical computational modeling. First, this work simulates a duplex microstructure matrix by a computational stochastic method. Subsequently, it uses this matrix to simulate the sigma phase's nucleation and growth. The Causal Cone method is the base of the nucleation and growth algorithm. The phase transformation code developed gave good results. The computational method calculates many parameters to evaluate microstructural development by stereological measurements. With the Linear Mixing Rule, the computational code predicts the material's mechanical properties. The study compares the data found in the literature against the numerical simulation outcomes. It was possible to verify the increase of the hardness for more significant volumetric fractions of sigma. The results present the transformed microstructure, the growth kinetic, and the mechanical properties evolution in time. This new technology saves money, time, sample, and human resources in carrying out a practical laboratory experiment.

Logistic matrix factorisation and generative adversarial neural network-based method for predicting drug-target interactions.

Identifying drug-target protein association pairs is a prerequisite and a crucial task in drug discovery and development. Numerous computational models, based on different assumptions and algorithms, have been proposed as an alternative to the laborious, costly, and time-consuming traditional wet-lab methods. Most proposed methods focus on separated drug and target descriptors, calculated, respectively, from chemical structures and protein sequences, and fail to introduce and extract features where the interaction information is embedded. In this paper, we propose a new three-step method based on matrix factorisation and generative adversarial network (GAN) for drug-target interaction prediction. Firstly, the matrix factorisation technique is used to capture and extract the joint interaction feature, for both drugs and targets, from the drug-target interaction matrix. Then, a GAN is introduced for data augmentation. It generates a fake positive sample similar to the real positive sample (known interactions) in order to balance the samples, allow the exploitation of the entire negative sample, and increase the data size for an accurate prediction. Finally, a fully connected four-layer neural network is built for classification. Experimental results illustrate a higher prediction performance of the proposed method compared to shallow classifiers and to state-of-the-art methods with an accuracy higher than 97%. Moreover, the data generation effect is confirmed by evaluating the proposed method with and without the generation step. These results demonstrated the efficiency of the latent interaction features and data generation on predicting new drugs or repurposing existing drugs. Overview of the WGANMF-DTI workflow for the Drug-Target Interaction Prediction task.

Numerical and experimental justification of transcatheter aortic valve prosthesis design

Objective: to justify the design of a self-expanding transcatheter aortic valve prosthesis based on a biomaterial stabilized with ethylene glycol diglycidyl ether using numerical simulation and a series of field experiments with working prototypes to determine the consistency of the proposed design solutions.Material and methods. Numerical computer models of a developed aortic valve prosthesis intended for transcatheter implantation, as well as prototypes of the most promising concepts for a series of field tests, were used in the work. Computer 3D models were subjected to numerical analysis in the Abaqus/CAE environment (Dassault Systemes, France) based on the finite element method with iterative design optimization and repeated numerical experiments. Physical prototypes of the transcatheter prosthesis were subjected to a series of mechanical tests for axial and radial compression, as well as tests on a Vivitro hydrodynamic stand (Vivitro Labs, Canada) under simulated normal flow. All studies were carried out in a comparative aspect with a similar transcatheter aortic valve prosthesis (control), the CoreValve™ bioprosthesis (Medtronic, Inc., USA).Results. Computer simulation demonstrates the stress-strain state values that do not significantly exceed the critical levels (628 and 756 MPa versus the threshold value 1080 MPa) for two basic concepts of support frames. The fatigue strength based on the calculation of the mean and alternating stresses corresponding to normo- and hypertensive states based on the Goodman diagrams, did not reveal any evidence that the threshold values (destruction area after 200 million cycles) were exceeded. The hydrodynamic characteristics of working prototypes made on the basis of computer models correspond to the testing data of CoreValve™ clinical bioprosthesis: the effective orifice area was 1.97 cm2, the mean transprosthetic gradient was 8.9 mm Hg, the regurgitant volume was 2.2–4.1 mL per cycle depending on the prototype model.Conclusion. Generally, experiments carried out showed the consistency of the concepts, including from the point of view of implementation of the leaflet apparatus based on xenogeneic tissues treated with ethylene glycol diglycidyl ether.