Simulation Of Development Research Articles

The use of social simulation modelling to understand adherence to diabetic retinopathy screening programs

The success of screening programs depends to a large extent on the adherence of the target population, so it is therefore of fundamental importance to develop computer simulation models that make it possible to understand the factors that correlate with this adherence, as well as to identify population groups with low adherence to define public health strategies that promote behavioral change. Our aim is to demonstrate that it is possible to simulate screening adherence behavior using computer simulations. Three versions of an agent-based model are presented using different methods to determine the agent’s individual decision to adhere to screening: (a) logistic regression; (b) fuzzy logic components and (c) a combination of the previous. All versions were based on real data from 271,867 calls for diabetic retinopathy screening. The results obtained are statistically very close to the real ones, which allows us to conclude that despite having a high degree of abstraction from the real data, the simulations are very valid and useful as a tool to support decisions in health planning, while evaluating multiple scenarios and accounting for emergent behavior.

Suppressive might of a few: T follicular regulatory cells impede auto-reactivity despite being outnumbered in the germinal centres.

The selection of high-affinity B cells and the production of high-affinity antibodies are mediated by T follicular helper cells (Tfhs) within germinal centres (GCs). Therein, somatic hypermutation and selection enhance B cell affinity but risk the emergence of self-reactive B cell clones. Despite being outnumbered compared to their helper counterpart, the ablation of T follicular regulatory cells (Tfrs) results in enhanced dissemination of self-reactive antibody-secreting cells (ASCs). The specific mechanisms by which Tfrs exert their regulatory action on self-reactive B cells are largely unknown. We developed computer simulations to investigate how Tfrs regulate either selection or differentiation of B cells to prevent auto-reactivity. We observed that Tfr-induced apoptosis of self-reactive B cells during the selection phase impedes self-reactivity with physiological Tfr numbers, especially when Tfrs can access centrocyte-enriched GC areas. While this aided in selecting non-self-reactive B cells by restraining competition, higher Tfr numbers distracted non-self-reactive B cells from receiving survival signals from Tfhs. Thus, the location and number of Tfrs must be regulated to circumvent such Tfr distraction and avoid disrupting GC evolution. In contrast, when Tfrs regulate differentiation of selected centrocytes by promoting recycling to the dark zone phenotype of self-reactive GC resident pre-plasma cells (GCPCs), higher Tfr numbers were required to impede the circulation of self-reactive ASCs (s-ASCs). On the other hand, Tfr-engagement with GCPCs and subsequent apoptosis of s-ASCs can control self-reactivity with low Tfr numbers, but does not confer selection advantage to non-self-reactive B cells. The simulations predict that to restrict auto-reactivity, natural redemption of self-reactive B cells is insufficient and that Tfrs should increase the mutation probability of self-reactive B cells.

Simulation Modeling of an Inhomogeneous Medium, in Particular: Round, Triangular, Square Shapes

The article analyzes and develops an algorithm for the operation of the powder backfill process using vibration oscillations. The results of the study make it possible to predict the main properties of particles of any shape. The developed computer simulation model also provides for the superposition of horizontal and vertical oscillations. It should be noted that the difference between them is that the main one for the implementation of horizontal oscillations is the X - coordinate, and for vertical ones – the Y - coordinate. It is also important that the model algorithm provides for simultaneous application of vibration oscillations, which makes it possible to study the influence of the history of the backfill process. It should also be noted that in this scientific study, a number of experiments were conducted, the change in porosity during the imposition of oscillations was studied, and graphs of the obtained experimental dependences were constructed. Porosity from the main parameters of the bunker, in particular: width and height, is also studied. The obtained results made it possible to record the optimal porosity of the backfill with a reliable deviation error (± 1%).

Nonlinear inelastic analysis of eccentrically loaded square high-strength concrete short columns incorporating steel equal-angles

Steel-Equal Angle (SEA) has recently been utilized as longitudinal reinforcement in high-strength concrete columns to improve their strength and ductility. However, investigations have been very limited on the responses of eccentrically loaded SEA Reinforced Concrete (SEARC) columns. This paper presents the development of a computer simulation model based on fiber element discretization for determining the structural behavior of eccentrically loaded SEARC short columns. The inelastic buckling of SEA sections and the concrete confinement induced by SEA sections are explicitly taken into account. The modeling procedures are given for axial load moment-interaction curves and moment-curvature curves of SEARC columns. The accuracy of the developed fiber model is verified against the available test data. The performance of eccentrically loaded SEARC columns incorporating various design parameters is extensively investigated. It is shown that the developed computer simulation model captures well the experimentally measured responses of short SEARC columns and can be utilized in the analysis and design of such columns in practice. It has been found that the behavior of SERAC columns under eccentric loads is significantly influenced by the longitudinal steel ratio, the compressive strength of concrete, and the axial load level. The width of SEA sections and tie spacing considerably influence the ductility of the columns.

Визначення оптимальної точки приєднання сонячної електростанції до електричної мережі методом комп’ютерного імітаційного моделювання

The purpose of this study is to minimize the negative impact of the solar power plant on the value of the steady voltage deviation and the level of electricity losses by determining the optimal place for its connection to the distribution network. Currently, quite a large number of methods of optimal placement of renewable sources of electricity in electrical networks have been developed. However, most of them either do not fully take into account the multifunctional influence of renewable energy sources on the parameters of the electric network regime, or are quite difficult to use. In order to solve the problem of optimal placement of renewable sources of electricity in electric networks, it is proposed to use the method of computer simulation modeling. The essence of this method is to determine the optimal place for connecting a renewable energy source to the electrical network based on the analysis of the results of computer simulation modeling of network mode parameters. This approach is the most acceptable in the case of connecting a solar power plant of average power to the electrical network of an industrial enterprise. The developed computer simulation model of a distribution electric network with a solar power plant allows for the research of network mode parameters, including the determination of the level of active power loss in network elements and the level of steady voltage deviation. The specified computer simulation models of the distribution electric network with a solar power plant made it possible to determine the optimal place for connecting the solar power plant based on the values of power losses in the elements of the electric network at the level of the established voltage deviation. The results of computer modeling of an electrical network with a solar power plant confirmed the need to take into account not only the values of the established voltage deviation, but also the amount of electrical energy losses in the network elements in the process of choosing a place to install a solar power plant. The results of the research can be used in solving the problems of determining the place of connection of a medium-power solar power plant to the electrical network of an industrial enterprise.

ІМІТАЦІЙНА КОМП'ЮТЕРНА МОДЕЛЬ ПРОЦЕСІВ РОЗПОВСЮДЖЕННЯ СИГНАЛІВ У КОАКСІАЛЬНОМУ КАБЕЛІ

Background. The paper studies processes of signal propagation in a coaxial cable as a type of artificial long lines. Utilization of analytical methods as well as natural experiments for analyzing these processes is rather difficult and not sufficiently descriptive. The aim of the paper is to develop a simulation computer model of coaxial cable represented as an artificial long line and to use this model for studying processes in it. Main attention is paid to clarify impact of irregularities in the line and matched signal transmission from the source to the load with minimal losses. Methods. Methods of computer simulation as well as complex systems analysis are used. Results. To achieve the set goal, the paper solves the tasks of a coaxial cable equivalent circuit design as an artificial long line, which includes signal source with a certain internal impedance, the line itself with a possibility to vary its parameters and the load; representation of the processes in the developed line with the help of Ohm’s and Kirchhoff’s laws in terms of differential equations of continuous time; transition from the system of differential equations to the one of difference in order to use them for computer simulation; design of a computer simulation model on the base of the obtained system of difference equations; and trial of the computer simulation model in the scenario of signal propagation in the long line with irregularities. Computer simulation results that are obtained in the paper completely correspond to the theoretical notions related to the processes in long lines in different modes of their operation. The results have allowed one to assess numerically and qualitatively, and most impotently descriptively, impact of irregularities in the line on the optimal signal transmission in it. Сonclusions. Developed computer simulation model of a coaxial cable as an artificial long line can be used for tuition processes at universities and for design and modernization of these devices. Keywords: simulation computer model, coaxial cable, artificial long line, line irregularities, matched signal transmission

COMPUTER SIMULATION MODEL OF A COMPUTER NETWORK WITH FRACTAL TRAFFIC FOR TESTING ROUTING ALGORITHMS


 
 
 The object of research in this article is simulation modeling of a computer network and the process of traffic routing. The relevance of the research is due to the importance of ensuring the quality of service in computer networks, in particular, by necessity reducing the number of lost IP-packets at high traffic intensity values. Determining the routing of traffic packets is a complex process and is based on various indicators or combinations of indicators. If the routing process takes place in a dynamic mode, then the complexity of the route calculation increases, in this case, one of the tools for research and comparison of different routing algorithms can be a computer simulation model of a computer network. The goal of the work is the development and research of a computer simulation model of a computer network for testing traffic routing algorithms. The tasks: to develop computer simulation model of a computer network to generate the network structure and simulate the traffic distribution process with the ability to test different routing algorithms. Research methods: theory of computer networks, theory of fractal analysis, object-oriented programming, theory of algorithms and data structures, theory of complex networks, theory of Markov processes. Conclusions. The paper investigated the basic principles of traffic routing in computer networks. A simulation model of a computer network for testing traffic routing algorithms has been developed. A method based on the theory of complex networks has been developed to generate the structure of a computer network. Theory of fractal analysis and Markov processes are used for traffic generation. A series of experiments was conducted on a developed model to determine how different fractal dimensions of traffic at high traffic intensity values affect the number of lost packets, and therefore the quality of service. Analyzing the results of the experiment, the following conclusions can be drawn: the least number of lost packets occurs when the process is random or has weak trends. The fewest lost packets were at fractal dimension 1.5, i.e., when the process is completely random, there were also few lost packets at fractal dimensions close to this; persistent and anti-persistent processes (those with memory) cause more packet loss for the same traffic intensity and maximum number of packets sent from one device per unit of time. Moreover, anti-persistent processes cause significantly more losses than persistent ones. Thus, when performing traffic routing and finding optimal paths for sending IP-packets, it can be useful to determine and take into account the fractal dimension of traffic at the entrance of each router and use it when calculating metrics to determine the best routes.
 
 

The Use of Double-Skin Façades to Improve the Energy Consumption of High-Rise Office Buildings in a Mediterranean Climate (Csa)

Engineers use double-skin façades (DSF) to lower the energy consumption of buildings as they can potentially control incoming wind speeds and the amount of solar heat gain. The purpose of this present study was to (1) evaluate the use of DSFs, (2) its efficacy in improving the energy performance of high-rise office buildings in the hot, dry summer climate of the Mediterranean, and (3) to develop an optimum DSF model for this climate based on industry standards and recommendations for high-performance DSF parameters. In order to determine the efficiency of DSFs, two distinct variables, building orientation and the number of DSFs used, were taken into consideration. This study adopted an experimental (generate and test) research design and used Autodesk® Ecotect® Analysis software to develop computer simulations with which to assess 15 single façades, juxtaposed façades, three façades, and four façades on cardinal orientations. The recorded energy consumption and savings were then compared with that of the reference model. The results indicated that the three DSF model, i.e., the S14 model, reduced energy consumption during heating by 28% and by 53.5% when cooling a high-rise office building located in the hot, dry summer climate of the Mediterranean (Csa).

Model-based Bayesian inference of the ventilation distribution in patients with cystic fibrosis from multiple breath washout, with comparison to ventilation MRI

BackgroundIndices of ventilation heterogeneity (VH) from multiple breath washout (MBW) have been shown to correlate well with VH indices derived from hyperpolarised gas ventilation MRI. Here we report the prediction of ventilation distributions from MBW data using a mathematical model, and the comparison of these predictions with imaging data. MethodsWe developed computer simulations of the ventilation distribution in the lungs to model MBW measurement with 3 parameters: σV, determining the extent of VH; V0, the lung volume; and VD, the dead-space volume. These were inferred for each individual from supine MBW data recorded from 25 patients with cystic fibrosis (CF) using approximate Bayesian computation. The fitted models were used to predict the distribution of gas imaged by 3He ventilation MRI measurements collected from the same visit. ResultsThe MRI indices measured (I1/3, the fraction of pixels below one-third of the mean intensity and ICV, the coefficient of variation of pixel intensity) correlated strongly with those predicted by the MBW model fits (r=0.93,0.88 respectively). There was also good agreement between predicted and measured MRI indices (mean bias ± limits of agreement: I1/3:−0.003±0.118 and ICV:−0.004±0.298). Fitted model parameters were robust to truncation of MBW data. ConclusionWe have shown that the ventilation distribution in the lung can be inferred from an MBW signal, and verified this using ventilation MRI. The Bayesian method employed extracts this information with fewer breath cycles than required for LCI, reducing acquisition time required, and gives uncertainty bounds, which are important for clinical decision making.

Putting Potential at the Core of Teaching Electric Circuits

Electricity has shaped modern civilization in a way few other discoveries have. Nonetheless, few students successfully develop a basic understanding of voltage, current, and resistance or their mutual relationship in simple DC circuits. Despite teachers’ best efforts in the classroom, so-called “alternative conceptions” often prevail after traditional instruction. In particular, voltage has proven to be a difficult concept to teach—many students erroneously think of voltage as a property of electric current. Furthermore, a battery is often considered to be a source of constant current rather than constant voltage. In order to help students develop a better understanding of simple DC circuits, we developed a new curriculum with an accompanying computer simulation that illustrates potential differences in circuits in order to make voltage rather than current the students’ primary concept when analyzing circuits. To this end, the curriculum takes typical alternative conceptions into account and builds on students’ everyday experiences with air pressure in order to provide them with an immediately tangible counterpart in electric potential. In analogy to air pressure differences that cause an air flow, voltage is introduced as an “electric pressure difference” that causes an electric current. Using the accompanying computer simulation, potential differences are visualized in simple DC circuits using color coding and a height representation. The new curriculum including teaching resources as well as the newly developed computer simulation are both freely available online to teachers and students alike.

Developing computer simulations for risk assessment by cable logging rigging crews

ABSTRACT This paper developed six cable logging incident scenarios that were modeled in a simulated environment, and conducted a pilot study in the Pacific Northwest to assess the potential for collecting worker risk assessment data. All the subjects in the pilot study reported that they understood the simulated incidents, and they were able to move around in the simulation to see what they needed. When reporting management requiring conditions (MRC) before performing the simulated task, the subjects consistently identified the first main MRC; however, there was variation in reporting the second main MRC. The results from the pilot study indicate that the simulations effectively modeled the spatial aspects of the incidents; however, the simulations lacked avatars to represent people in the simulations and this may have limited the ability to include cognitive aspects such as communication. Variation in the severity assigned by the subjects to the MRC, and to the unexpected events, revealed important differences in risk sensitivity between the subjects, and the importance of experiential learning in a safe environment when considering energized systems.

Pulse­forming network with damping resistors

The paper is dealing with the processes in pulse-forming networks, which are used in pulse modulators of different radio-technical installations. It is stressed, that the main problem that the designers of the pulse-forming networks face is to secure required form of the pulse under conditions of the network discharge over the matched load. In the previous paper, to improve the form of this pulse, it was proposed to use damping resistor connected in parallel to the first inductance. In this case, it was demonstrated that under optimal choice of the network damping resistor and the first capacitor parameters, maximum relative deviation of the modulator pulse amplitude from the expected value decreases approximately 12 times. In the current paper, to study possibilities of the further decrease of the relative deviation of the pulse amplitude from the expected value, it is proposed to also use damping resistor connected in parallel to the second inductance of the network. To perform the mentioned research, the previously developed computer simulation model was perfected with account of adding to the network diagram of the damping resistor in parallel with the second inductance. Trials of the improved computer simulation model with two damping resistors proved that while connecting the resistor in parallel to the second network inductance and tuning the value of the capacitor of the network, relative deviation of the pulse amplitude from the expected value decreases from 0.8 to 0.5 per cent. This pulse form amelioration appears to be sufficiently big, taking into account negligible cost of the elements that are added to the pulse-forming network. Proposed and researched with the help of developed and improved computer simulation model pulse-forming network can be used in pulse modulators of different radio-technical installations, in telecommunication networks and radiolocation. This is especially relevant for those pulse modulators that feed power amplifiers sensitive to the deviation of the voltage of the pulse power supply.

Computer modeling of cardiac rhythm based on vector of stationary random sequences

The article is devoted to a computer modeling method of electrocardiogram rhythm based on a mathematically justified model in the form of a vector of stationary random sequences. The developed computer modeling method allows for generating realizations of vector electrocardiogram rhythm signal (vector components of stationary random sequences) for different types of electrocardiogram signals, both normal and with various types of rhythm pathologies. The modeling of electrocardiogram rhythms was carried out based on the obtained statistical information in the form of estimates of the mathematical expectation and variance of the components of the vector of stationary random sequences. It has been shown that the obtained estimates of statistical characteristics of the modeled vector components (components that describe the electrocardiogram rhythm) are within confidence intervals, which is an indication of the correctness of the experiments conducted using the developed computer simulation method. The accuracy of the computer simulation method for generating realizations of the vector components of stationary random sequences has been investigated, and the error of the computer simulation does not exceed 13% for the investigated vector components.

Photon Recycling Effect and Lossless Fluorescence Propagation in β‐Sheet Peptide Fibers

AbstractLight‐delivering optical fibers are widely used for biomedical imaging, theranostics and surgery, and optogenetics. In this work, a new generation of bioinspired optical fibers is proposed. Developed amyloidogenic peptide fibrillary structures with tailored β‐sheet conformation exhibit unique optical properties of full overlapping of broadband visible fluorescence (FL) and optical absorption spectra. This study reports on unexpected lossless propagation of the FL light along 100 µm length β‐sheet microfibers. It is shown that the found FL long‐distance lossless radiative energy transport occurs due to highly effective FL photon recycling phenomenon supported by FL zero Stokes shift and high quantum yield. This new non‐Beer–Lambert FL lossless propagation mechanism is observed in very thin ≈1 µm diameter fibers, providing a single/few‐mode waveguiding regime. The developed model and computer simulations, based on the finite difference time domain method, are consistent with the experimental results. Fabricated peptide FL fiber probes permit delivering intensity‐modulated FL signal with selected wavelength over the whole visible spectrum in wide modulation frequencies range.

A METHOD OF COMPUTER SIMULATION MODELING OF USER AND BOT BEHAVIOR IN A RECOMMENDATION SYSTEM USING THE GRAPH DATABASE NEO4J

The subject matter of the article is the process of computer simulation modeling of complex networks. The goal is to develop a method of computer simulation modeling of ordinary user and bot behavior in a recommendation system based on the theory of complex networks to test the accuracy and robustness of various algorithms for generating recommendations. The tasks to be solved are: to develop a computer simulation model of user and bot behavior in a recommendation system with the ability to generate datasets for testing recommendation generation algorithms. The methods used are: graph theory, theory of complex networks, statistics theory, probability theory, methods of object-oriented programming and methods of working with graph databases. Results. A method of computer simulation modeling of users and objects in a recommender system was proposed, which consists of generating the structure of the social graph of a recommender system and simulating user and bot behavior in it. A series of experiments to test the performance of the developed computer simulation model was carried out. During the experiments, working and testing datasets were generated. Based on the working datasets, the preferences of users by the method of collaborative filtering were predicted. Based on testing datasets, the accuracy of prediction predictions was checked. The results of the experiments showed that the jitter of the investigated values of the Precision, Recall and RMSE of prediction predictions in most practical cases confidently fits within the allowable fluctuation limits, and therefore the users' behavior in computer simulation model was not random and it real users' behavior with certain preferences was simulated. This confirms the reliability of the developed computer simulation model of a recommendation system. Conclusions. A method of computer simulation modeling of user and bot behavior in a recommendation system, which allows generating datasets for testing the algorithms for generating recommendations, was proposed. The developed method makes it possible to simulate the behavior of both ordinary users and bots, which makes it possible to create datasets for testing the robustness of recommender systems to information attacks, as well as for testing the effectiveness of methods for detecting and neutralizing botnets. The structure of relations between users and objects of the recommender system was modeled using the theory of complex networks. Information attacks of bots were modeled on the basis of known models of profile-injection attacks on recommender systems.

Computer simulation of microstructure development in powder-bed additive manufacturing with crystallographic texture

Parts produced via laser powder-bed fusion additive manufacturing exhibit complex microstructures that depend on processing variables and often vary widely in crystallographic texture and grain morphology. The need to understand, predict, and control these microstructural variations motivates the development of modeling tools capable of accurately predicting LPBF microstructures. Monte Carlo (MC) Potts models have been employed to successfully model the formation of grain structures in additively manufactured parts but have lacked the ability to simulate crystallographic texture. We present an extension of the MC Potts model that assigns an orientation to each grain and penalizes growth of solid into the fusion zone based on proximity of the nearest 〈100〉 crystal direction to the local temperature gradient direction. This allows for crystallographically selective growth to drive texture formation during the development of the solidification microstructure in each melt track. LPBF builds of alloy 718 with a unidirectional scan pattern provided microstructures with substantial variations in grain size, grain morphology, and texture. These distinctive albeit atypical microstructures were used to validate the simulation method, i.e. good agreement was obtained between the simulated and experimental grain shapes and textures.

A Computer Tool for Modelling CO2 Emissions in Driving Tests for Vehicles with Diesel Engines

The dynamic development of transport in recent decades reflects the level of economic development in the world. The transport sector today is one of the main barriers to the achievement of the European Union’s climate protection objectives. More and more restrictive legal regulations define permissible emission limits for the amounts of toxic substances emitted into the atmosphere. Numerical CO2 modeling tools are one way to replace costly on-road testing. Driving cycles, which are an approximation of the vehicle’s on-road operating conditions, are the basis of any vehicle approval procedure. The paper presents a computer tool that uses neural networks to simulate driving tests. Data obtained from tests on the Mercedes E350 chassis dynamometer were used for the construction of the neural model. All the collected operational parameters of the vehicle, which are the input data for the built model, were used to create simulation control runs for driving tests: Environmental Protection Agency, Supplemental Federal Test Procedure, Highway Fuel Economy Driving Schedule, Federal Test Procedure, New European Driving Cycle, Random Cycle Low, Random Cycle High, Mobile Air Conditioning Test Procedure, Common Artemis Driving Cycles, Worldwide Harmonized Light-Duty Vehicle Test Procedure. Using the developed computer simulation tool, the impact on CO2 emissions was analyzed in the context of driving tests of four types of fuels: Diesel, Fatty Acid Methyl Esters, rapeseed oil, butanol (butyl alcohol). As a result of the processing of this same computer tool, mass consumption of fuels and CO2 emissions were analyzed in driving tests for the given analyzed vehicle.

Cells image generation method based on VAE-SGAN

Abstract Although it has entered the era of big data, the image data with important research value in the field of medical imaging is often scarce due to various reasons such as difficult acquisition. To increase the image data in these fields, people have developed computer simulations to generate images Methodological research. At present, there are two main types of image generation models with potential, namely, Variational Autoencoders (VAE) [1] and Generative Adversarial Networks (GAN) [2]. In the process of classifying white blood cells, there are often insufficient sample data and unbalanced data. How to effectively expand the sample size and solve the imbalance of training data has always been a hot issue in research. In order to solve this problem, this paper proposes an image generation method based on the fusion network of VAE and GANs, which avoids the shortcomings of the two generation methods when used alone, and makes the generated images have higher generation quality.

Computer modeling of the results of laboratory studies of the development of internal corrosion of steel pipes

Discusses the development of corrosion in steel pipes. The results of computer simulation of internal corrosion development in various sections of steel pipes are presented.

Time-domain coupled dynamic simulation for SFT-mooring-train interaction in waves and earthquakes

In this study, Submerged Floating Tunnel (SFT)-mooring-train coupled dynamics is solved in the time domain to investigate their dynamic and hydro-elastic interactions under wave and earthquake excitations. The SFT is modeled by the rod-FE (finite element) theory, and it is connected to mooring lines through dummy-connection-mass and linear and rotational springs. A 3D rigid-multi-body dynamic model is developed for train dynamics that consists of seven rigid bodies. The tunnel-train interaction is taken into consideration based on the wheel-rail correspondence assumption and the simplified Kalker linear creep theory. The developed computer simulation program is validated through comparisons with commercial programs and published results when possible. In the case of earthquake-induced dynamics of the coupled system, the effects of soil conditions, tunnel length, mooring interval, seismic-wave propagation, and seaquake are investigated. The magnitudes of the SFT downward motions induced by the moving train are small compared with the motions induced by earthquakes. The earthquake causes transient SFT responses especially at their lowest wet natural frequencies while high-frequency motions are induced by seaquake effect. Structural damping and seismic propagation play an important role in dynamic responses. The interaction of the tunnel and moving train is also evaluated for various train speeds in terms of the derailment and offload factors and riding-comfort criterion. For the given SFT and train designs, the offload factor and riding-comfort criterion can slightly exceed their limits at certain earthquake conditions with the speed as high as 70 m/s, which can be adjusted by reducing train speed.