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Abstract Constructivist learning theories consider deep understanding of the content to be the result of engagement in relevant learning activities with appropriate scaffolding that provides the learner with timely and substantive feedback. However, any group of students has a variety of levels of knowledge and cognitive development, which makes providing appropriate individual-level scaffolding and feedback challenging in the classroom. Computer simulations can help meet this challenge by providing technology-enhanced embedded scaffolding and feedback via specific simulation design. The use of computer simulations does not, however, guarantee development of deep science understanding. Careful research-driven design of the simulation and the accompanying teaching structure both play critical roles in achieving the desired learning outcomes. In this paper, we discuss the capabilities of computer simulations and the issues that can impact the learning outcomes when combining technology-enhanced scaffolding and feedback with external teaching structures. We conclude with suggestions of promising research avenues on simulation design and their use in the classroom to help students achieve deep science understanding.

The research shows how to use swarming algorithms to rebuild the heat transfer coefficient, especially in regard to the continuous border condition. The authors utilized their application software to do numerical computations, employing classical variants of swarm algorithms. The numerical calculations employed a functional determining error to assess the accuracy of the estimated result. The functional minimization was conducted with the swarm algorithms (especially ABC and ACO). The geometry analyzed in this study consisted of a square shape referred to as the cast, enclosed within another square shape known as the casting mold. These two squares were separated by a layer facilitating heat conduction, characterized by the coefficient κ. The coefficient of the thermally conductive layer was recalibrated utilizing swarm methods within the range of 900 - 1500 [W/m^2K] and subsequently compared to a predetermined reference value. A finite element mesh consisting of 576 nodes was used for the calculations. The study involved simulations with populations of 5, 10, 15, and 20 individuals. Furthermore, each scenario also took into account noise of 0%, 2%, and 5% of the reference values. Results make evident the reconstructed value of the κ coefficient, cooling curves, and temperatures for the ABC and ACO algorithms are physically correct. The consequences indicate a notable level of satisfaction and strong concurrence with the anticipated of the κ parameter values. The results from the numerical simulations demonstrate considerable promise for applying artificial intelligence algorithms in optimizing production processes, analyzing data, and facilitating data-driven decision-making.

Paper-based microfluidics has emerged as a promising field with diverse applications ranging from medical diagnostics to environmental monitoring. Despite significant progress in research and development, the translation of paper-based prototypes into practical end-user devices remains limited. This limitation stems from challenges related to devices not being sufficiently portable and autonomous, which paper-based microfluidics is expected to overcome. Yet for this purpose, we note the lack of comprehensive numerical modeling tools capable of simulating the intricate physicochemical phenomena involved in order to optimize the development process; hence, in this study, we introduce porousMicroTransport, a novel simulation package integrated with the open-source platform OpenFOAM®, designed to address these challenges. porousMicroTransport offers efficient solvers for fluid flow and transport phenomena in microfluidic porous media, including capillarity models and (bio)chemical reactions. Moreover, under horizontal flow conditions, porousMicroTransport application field can be extended to any porous media. We demonstrate the software’s effectiveness in two example cases, showcasing its ability to accurately reproduce complex phenomena involved in paper-based devices. By virtue of being an easy-to-use and computationally efficient tool, porousMicroTransport facilitates the design and optimization of devices, potentially enabling more devices to meet the WHO’s REASSURED criteria for point-of-care testing. We anticipate that this tool will accelerate the development and deployment of robust and portable diagnostic devices, bridging the gap between research and practical applications.

This work contributes to the comprehension of Bayes’ theorem inclusive Bayesian probabilities and Bayesian inferencing within the framework of STEM (Science, Technology, Engineering, Arts, and Mathematics) and cognitive learning w.r.t Bloom’s taxonomy (BT). Bayes’ theorem is taken as a crucial statistical instrument employed in the development of intelligent systems and the management of risks, commonly utilized by engineers for tasks in machine learning and managerial decision-making. The fundamental concept behind Bayes’ theorem revolves around comprehending the degree of truth within the confines of an explicit perspective. This involves partitioning the entire sample space of possible evidence and utilizing the subset containing the relevant perspective to estimate the uncertainty of an event or the reliability of a model. However, it is often found difficult for students to understand Bayes’ theorem to the level of applying it to real-world problems. Considering this, the proposed learning method in this paper elucidated the acquisition of Bayes’ mathematical formulation by leveraging computational thinking, leading to the development of a computational model. The proposed model is named the Bayesian Computational Learning Model (BCLM). Subsequently, we have probed the utility of BCLM in the design and plan of learning activities, coherent to the STEM paradigm and BT cognitive learning hierarchy.

Air pollution is currently the most significant environmental factor posing a threat to the health and lives of European residents. It is a key cause of poor health, particularly respiratory and cardiovascular diseases. The primary aim of the study was to numerically determine the impact of the air purifier model’s geometry on the distribution of air within a room and to conduct experimental tests on the filtration efficiency and preliminary antibacterial activity of filtration composites. The scope of the work included designing an air purifier model in the form of a pendant lamp and performing computer simulations in Ansys software to identify the optimal shape. The experimental research focused on developing filtration composites consisting of nonwoven fabric with an active hydrosol layer, meltblown nonwovens and a carbon filter. The study results showed that the SMMS composite with 50% thyme and carbon nonwoven exhibited the highest filtration efficiency for both small and large particles.

Normal log lengths in Norway are 3-6 m (NL), but occasionally there is a demand for short timber with a 2.5 m log length (ST). There are concerns that ST could reduce the forwarders' productivity. Six type stands were created based on harvester data. Different assortment distributions, conditions, and forwarders were simulated in each type stand. It was found that an additional ST assortment almost always decreased productivity (from -15.5 to +4%). Increased forwarding distance (m), more difficult driving conditions, and increased log concentration [m3.(100 m strip road)-1] decreased the productivity difference between sites with ST and NL and sites with only NL. Increased forwarder size increased the productivity difference between sites with ST and NL and sites with only NL. It is possible to load two stacks of ST on some forwarders. Such loading was more productive than loading one stack on longer forwarding distances, while the opposite was the case on short distances. However, loading two stacks of ST can lead to overloading.

A mathematical model of the spatial distribution of the radiation flux in a multimode Hermite-Gaussian beam is proposed. In this model, the spatial distribution of the radiation flux is described by rays with radiation fluxes strung on them. A feature of the proposed model is that the radiation fluxes strung on the beams are added algebraically.

As the functionality of modern digital societies is largely based on interactive digital technology, educational technology has inevitably gone through a process of digitalization. Studying information technology, computer science, or computer engineering in the post-digital era makes it very hard for students to disjoin personal technology needs, learning necessities, and future career demands, putting them at great risk for developing psychological disorders. The aim of this international comparative study is to examine the effects of interactive digital technology exposure on learning performance in computer graphics and simulations. To conduct a comparison of the 397 generation Z students from Greece and Serbia, a study was conducted evenly representing various geographic, economic, and socio-cultural environments. The research was realized between October 2021 and May 2022. The type of preferred gaming device was the most important digital technology exposure predictor of learning performance factors gain both in Greece and Serbia. Unexpectedly, digital gaming exposure and Internet gaming disorder were not significant predictors of academic success. The resulting model dually provides teachers with the opportunity to adapt their activities more efficiently and students with a self-diagnostic tool helping them to improve learning performance in the field of computer graphics and simulations more effectively.

Background: Clinical and experimental data on the cardiac effects of acute hypernatremia are scarce and inconsistent. We aimed to determine and understand the effects of different levels of acute hypernatremia on the human ventricular action potential. Methods: We performed computer simulations using two different, very comprehensive models of the electrical activity of a single human ventricular cardiomyocyte, i.e., the Tomek–Rodriguez model following the O’Hara–Rudy dynamic (ORd) model and the Bartolucci–Passini–Severi model as published in 2020 (known as the ToR-ORd and BPS2020 models, respectively). Mild to extreme levels of hypernatremia were introduced into each model based on experimental data on the effects of hypernatremia on cell volume and individual ion currents. Results: In both models, we observed an increase in the intracellular sodium and potassium concentrations, an increase in the peak amplitude of the intracellular calcium concentration, a hyperpolarization of the resting membrane potential, a prolongation of the action potential, an increase in the maximum upstroke velocity, and an increase in the threshold stimulus current at all levels of hypernatremia and all stimulus rates tested. The magnitude of all of these effects was relatively small in the case of mild to severe hypernatremia but substantial in the case of extreme hypernatremia. The effects on the action potential were related to an increase in the sodium–potassium pump current, an increase in the sodium–calcium exchange current, a decrease in the rapid and slow delayed rectifier potassium currents, and an increase in the fast and late sodium currents. Conclusions: The effects of mild to severe hypernatremia on the electrical activity of human ventricular cardiomyocytes are relatively small. In the case of extreme hypernatremia, the effects are more pronounced, especially regarding the increase in threshold stimulus current.

This study aimed to evaluate the financial feasibility of rainwater harvesting and greywater reuse in a multifamily building located in Florianópolis, Brazil. A building, consisting of two blocks with 60 flats each, was chosen to obtain data about the number of residents, building characteristics, potable water consumption, and rainwater and greywater demands (obtained by means of questionnaires and water measurements). The financial feasibility analyses considered rainwater and greywater systems separately and together. The impact on the urban stormwater drainage system was evaluated through the reduction of stormwater runoff. The energy consumption in the operational phase of each system was estimated through the amount of energy consumed by the motor pumps to supply one cubic meter of water. The potential for potable water savings through the use of rainwater—that supplies water for washing machines—was approximately 6.9%. The potential for potable water savings through the use of greywater—that supplies water to toilets—was approximately 5.7%. Both systems were feasible. The payback period for rainwater harvesting systems ranged from 57 to 76 months. For greywater systems, the payback period ranged from 127 to 159 months. When considering both systems working together, the payback period ranged from 89 to 132 months. The rainwater harvesting system can reduce 11.8% the stormwater volume destined to the urban stormwater drainage system in relation to the current contribution volume. Energy consumption was approximately 0.56 kWh/m3 of treated water for the rainwater harvesting system and 0.89 kWh/m3 of treated water for the greywater system. Rainwater and greywater were considered economically feasible, especially for higher inflation scenarios. Furthermore, such systems are interesting alternatives in terms of impacts considering urban drainage and energy consumption.

In injured arteries, platelets adhere to the subendothelium and initiate the coagulation process. They recruit other platelets and form a plug that stops blood leakage. The formation of the platelet plug depends on platelet activation, a process that is regulated by intracellular calcium signaling. Using an improved version of a previous multiscale model, we study the effects of changes in calcium signaling on thrombus growth. This model utilizes the immersed boundary method to capture the interplay between platelets and the flow. Each platelet can attach to other platelets, become activated, express proteins on its surface, detach, and/or become non-adhesive. Platelet activation is captured through a specific calcium signaling model that is solved at the intracellular level, which considers calcium activation by agonists and contacts. Simulations reveal a contact-dependent activation threshold necessary for the formation of the thrombus core. Next, we evaluate the effect of knocking out the P2Y and PAR receptor families. Further, we show that blocking P2Y receptors reduces platelet numbers in the shell while slightly increasing the core size. An analysis of the contribution of P2Y and PAR activation to intraplatelet calcium signaling reveals that each of the ADP and thrombin agonists promotes the activation of platelets in different regions of the thrombus. Finally, the model predicts that the heterogeneity in platelet size reduces the overall number of platelets recruited by the thrombus. The presented framework can be readily used to study the effect of antiplatelet therapy under different physiological and pathological blood flow, platelet count, and activation conditions.

Spectral line shapes code in plasmas (SLSPs) code comparison workshops have been organized in the last decade with the aim of comparing the spectra obtained with independently developed analytical and numerical models. Here, we consider the simultaneous effect of a plasma microfield and a periodic electric field on the hydrogen lines Lyman-α, Lyman-β, Balmer-α, and Balmer-β for plasma conditions where the Stark effect usually dominates line broadening.

Cyclic dinucleotides (CDNs) are cyclic molecules consisting of two nucleoside monophosphates linked by two phosphodiester bonds, which act as a second messenger and bind to the interferon gene stimulating factor (STING) to activate the downstream signaling pathway and ultimately induce interferon secretion, initiating an anti-infective immune response. Cyclic dinucleotides and their analogs are lead compounds in the immunotherapy of infectious diseases and tumors, as well as immune adjuvants with promising applications. Many agonists of pathogen recognition receptors have been developed as effective adjuvants to optimize vaccine immunogenicity and efficacy. In this work, the binding mechanism of human-derived interferon gene-stimulating protein and its isoforms with cyclic dinucleotides and their analogs was theoretically investigated using computer simulations and combined with experimental results in the hope of providing guidance for the subsequent synthesis of cyclic dinucleotide analogs.

Abstract Variance in reproductive success (sk2, with k = number of offspring) plays a large role in determining the rate of genetic drift and the scope within which selection acts. Various frameworks have been proposed to parse factors that contribute to sk2, but none has focused on age‐specific values of ϕ=sk2/k¯, which indicate the degree to which reproductive skew is overdispersed (compared to the random Poisson expectation) among individuals of the same age and sex. Instead, within‐age effects are generally lumped with residual variance and treated as “noise.” Here, an ANOVA sums‐of‐squares framework is used to partition variance in annual and lifetime reproductive success into between‐group and within‐group components. For annual reproduction, the between‐age effect depends on age‐specific fecundity (bx), but relatively few empirical data are available on the within‐age effect, which depends on ϕx. By defining groups by age‐at‐death rather than age, the same ANOVA framework can be used to partition variance in lifetime reproductive success (LRS) into between‐group and within‐group components. Analytical methods are used to develop null‐model expectations for random contributions to within‐group and between‐group components. For analysis of LRS, random variation in longevity appears as part of the between‐group variance, and effects (if any) of skip breeding and persistent individual differences contribute to the within‐group variance. Simulations are used to show that the methods for variance partitioning are asymptotically unbiased. Practical application is illustrated with empirical data for annual reproduction in American black bears and lifetime reproduction in Dutch great tits. Results show that overdispersed within‐age variance (1) dominates annual sk2 in both male and female black bears, (2) is the primary factor that reduces annual effective size to a fraction of the number of adults, and (3) represents most of the opportunity for selection. In contrast, about a quarter of the variance in LRS in great tits can be attributed to random variation in longevity, and most of the rest is due to modest differences in fecundity with age estimated for a single cohort of females. R code is provided that reads generic input files for annual and lifetime reproductive success and allows users to conduct variance partitioning with their own data.

Abstract Maturation of functional liquid‐like biomolecular condensates into solid‐like aggregates has been linked to the onset of several neurodegenerative disorders. Low‐complexity aromatic‐rich kinked segments (LARKS) contained in numerous RNA‐binding proteins can promote aggregation by forming inter‐protein β‐sheet fibrils that accumulate over time and ultimately drive the liquid‐to‐solid transition of the condensates. Here, atomistic molecular dynamics simulations are combined with sequence‐dependent coarse‐grained models of various resolutions to investigate the role of LARKS abundance and position within the amino acid sequence in the maturation of condensates. Remarkably, proteins with tail‐located LARKS display much higher viscosity over time than those in which the LARKS are placed toward the center. Yet, at very long timescales, proteins with a single LARKS—independently of its location—can still relax and form high viscous liquid condensates. However, phase‐separated condensates of proteins containing two or more LARKS become kinetically trapped due to the formation of percolated β‐sheet networks that display gel‐like behavior. Furthermore, as a work case example, they demonstrate how shifting the location of the LARKS‐containing low‐complexity domain of FUS protein toward its center effectively precludes the accumulation of β‐sheet fibrils in FUS‐RNA condensates, maintaining functional liquid‐like behavior without ageing.

Abstract Kiln geometries were developed to reach homogeneous temperatures above 900 °C, during the firing process, aiming to improve the production process of the ceramists from Vale do Jequitinhonha (MG/Brazil). Techniques of reactive flow numerical solution using the software Ansys CFX have been used to foresee the behavior of the firings. Two types of catenary geometries, simple and robust, were studied, capable of being easily reproduced. The firewood used as an energy source in the current kilns and the developed ones, in this research project, favored the control of the kiln’s atmosphere during the firing, beyond being a source found with easiness for the ceramists. The results of the numerical simulations demonstrated the energy efficiency of the kilns and the level of temperature reached. Knowing well thermal and gas dynamic behavior, some parameters of the burning could be improved, aiming for a better quality of used ceramics.

In this paper, we studied the internal structure of beetle elytra, i.e., three different structural forms of bio-inspired honeycomb column thin-walled structure (BHTS) to make the honeycomb sandwich structure commonly applied in engineering have better mechanical and lightweight performance. We choose the AlSi10Mg aluminum alloy as material specimens for fabrication using selective laser melting of additive manufacturing (AM-SLM) and testing. Considering the influence of strain rate effect (SRE) on the structure during impact loading, the numerical model was verified by uniaxial compression tests and numerical simulations. Then the effects of five different strain rates (100 s−1, 200 s−1, 300 s−1, 400 s−1 and 500 s−1) were discussed on the loading process of BHTSs specimens. The experimental results show that the energy absorption (EA) indexes of each BHTS are greatly improved by SRE in the out-of-plane compression test of AM-SLM AlSi10Mg: the initial peak crushing force (PCF), mean crushing force (MCF) and specific energy absorption (SEA) of the specimen average increased by 120.64 %, 8.74 % and 10.61 %, respectively. Finally, according to the evaluation of each EA indexes, the design of BHTS-Ⅲ has better comprehensive performance. These results can provide important assist for the design, manufacture and modeling of BHTS-based materials.

Spinodal phase separation in SMART (Self-passivating Metal Alloys with Reduced Thermo-oxidation) materials based on binary W-Cr with alloying elements Y and Zr is systematically investigated by a combination of Density Functional Theory with Cluster Expansion Hamiltonian and large-scale Monte Carlo simulations with thermodynamic integration. Comparing alloys of Zr with those of Y in ternary compositions with W and Cr, it is shown that there is a significant difference in the average short-range order between W and Zr, which changes from positive to negative from 500 K to higher temperatures in W70Cr29Zr1 alloys compared with the positive SRO (Short-Range Order) between W and Y in W70Cr29Y1 alloys at all temperatures. This change, however, does not affect the segregation behavior between W and Cr in the whole range of temperature between these alloys. Importantly, it is found that co-segregation of Y and Zr due to the negative SRO between them, in W70Cr29Y0.5Zr0.5 and W70Cr28Y1Zr1 considered alloys, increases the W-Cr positive SRO closer to the binary W70Cr30. Our modeling results reveal a significant impact on spinodal phase segregation of W and Cr in designing SMART materials for DEMO devices of future fusion power plants. Findings from recent experimental studies validate the modeling results, particularly the high-temperature behavior of the W-Cr-Zr alloys and the microstructure evolution of the W-Cr-Y-Zr alloys. The results provide a fundamental understanding of the radiation resistance phenomena observed in recent experiments on neutron-irradiated self-passivating alloys.

Guanylate binding proteins (GBPs) are soluble dynamin-like proteins that undergo a conformational transition for GTP-controlled oligomerization and disrupt membranes of intracellular parasites to exert their function as part of the innate immune system of mammalian cells. We apply neutron spin echo, X-ray scattering, fluorescence, and EPR spectroscopy as techniques for integrative dynamic structural biology to study the structural basis and mechanism of conformational transitions in the human GBP1 (hGBP1). We mapped hGBP1’s essential dynamics from nanoseconds to milliseconds by motional spectra of sub-domains. We find a GTP-independent flexibility of the C-terminal effector domain in the µs-regime and resolve structures of two distinct conformers essential for an opening of hGBP1 like a pocket knife and for oligomerization. Our results on hGBP1’s conformational heterogeneity and dynamics (intrinsic flexibility) deepen our molecular understanding relevant for its reversible oligomerization, GTP-triggered association of the GTPase-domains and assembly-dependent GTP-hydrolysis.

The present study focused on CO _2 capture, storage, and conversion through the innovative integration of plasma–ionic liquid (IL) technology. For the first time, we employed plasma-IL technology to confront climate change challenges. We utilized 1-Butyl-3-methylimidazolium chloride IL to capture and store CO _2 under atmospheric pressure, and subsequently employed plasma to induce the transformation of IL-captured CO _2 into CO. Furthermore, we performed computer simulations to enhance our understanding of the CO _2 and CO capture processes of water and IL solutions. This comprehensive approach provides valuable insights into the potential of plasma–IL technology as a viable solution for climate change.

In this communication, we describe the application of Boltzmann kinetic equations for modeling massive electronic excitation in a silicon nanocrystal film after its irradiation with intense femtosecond hard X-ray pulses. This analysis was inspired by an experiment recently performed at the X-ray free-electron laser facility SACLA, which measured a significant reduction in atomic scattering factors triggered by an X-ray pulse of the intensity ∼1019 W/cm2, occurring on a timescale comparable with the X-ray pulse duration (6 fs full width at half maximum). We show that a Boltzmann kinetic equation solver can accurately follow the details of the electronic excitation in silicon atoms caused by such a hard X-ray pulse, yielding predictions in very good agreement with the experimental data.

Co-adsorption of multi-components in ZrCo-based hydrogen storage materials can lead to a number of synergistic effects, such as the modification of adsorption sites, and further worsen the hydrogen storage capability. In this work, we explore the co-adsorption of H and CO on the ZrCo(110) surface and find that the molecular CO can be adsorbed on the clean alloy surface and thus decrease the hydrogen storage ability of the alloy. Moreover, CO occupies the adsorption site of H and therefore prevents the adsorption and diffusion into the interior of the lattice. Fortunately, the Hf dopant reduces the number of adsorption sites of the CO molecule and inhibits the formation of carbides to a certain extent. In addition, the partial density of states (PDOS) result shows that there is almost no interaction between the s orbital of H and the s orbital of Co on the pure surface of pre-adsorbed CO, while on the Hf-doped surface of pre-adsorbed CO, the s orbital of H overlapped greatly with the s orbital of Co, indicating that Hf doping inhibits CO toxicity in the interaction between H and the surface. Hence, the doping of Hf has the effect of giving resistance to CO toxicity and is conducive to the adsorption of H.

The intensive development of nanodevices acting as two-state systems has motivated the search for nanoscale molecular structures whose long-term conformational dynamics are similar to the dynamics of bistable mechanical systems such as Euler arches and Duffing oscillators. Collective synchrony in bistable dynamics of molecular-sized systems has attracted immense attention as a potential pathway to amplify the output signals of molecular nanodevices. Recently, pyridine-furan oligomers of helical shape that are a few nanometers in size and exhibit bistable dynamics similar to a Duffing oscillator have been identified through molecular dynamics simulations. In this article, we present the case of dynamical synchronization of these bistable systems. We show that two pyridine-furan springs connected by a rigid oligomeric bridge spontaneously synchronize vibrations and stochastic resonance enhances the synchronization effect.

In the life sciences, the use of mathematical modelling and computer simulation methods has brought many benefits. This is the case, for example, in physics. Biology makes very little use of these methods. One of the reasons for this may be that the biology teaching process is conducted in such a way that it discourages young people with an interest in mathematics and computer science. We propose to support the process of teaching biology by introducing simple elements of mathematical modelling of ecological processes. In this work, we showed what benefits would be the application of the NetLogo program in teaching biology in secondary schools. NetLogo is a multi-agent programming language designed to simulate complex phenomena. It is intended for both research and education and is used in a wide variety of scientific disciplines. We used the NetLogo program to create a model of searching for food by ants. We have shown that teaching biology by building a computer model forces a deeper understanding of the problem we are working on and uses and develops the creative abilities of young people.

In this study, we explore the simulation setup in computational neuroscience. We use GENESIS, a general purpose simulation engine for sub-cellular components and biochemical reactions, realistic neuron models, large neural networks, and system-level models. GENESIS supports developing and running computer simulations but leaves a gap for setting up today's larger and more complex models. The field of realistic models of brain networks has overgrown the simplicity of earliest models. The challenges include managing the complexity of software dependencies and various models, setting up model parameter values, storing the input parameters alongside the results, and providing execution statistics. Moreover, in the high performance computing (HPC) context, public cloud resources are becoming an alternative to the expensive on-premises clusters. We present Neural Simulation Pipeline (NSP), which facilitates the large-scale computer simulations and their deployment to multiple computing infrastructures using the infrastructure as the code (IaC) containerization approach. The authors demonstrate the effectiveness of NSP in a pattern recognition task programmed with GENESIS, through a custom-built visual system, called RetNet(8 × 5,1) that uses biologically plausible Hodgkin–Huxley spiking neurons. We evaluate the pipeline by performing 54 simulations executed on-premise, at the Hasso Plattner Institute's (HPI) Future Service-Oriented Computing (SOC) Lab, and through the Amazon Web Services (AWS), the biggest public cloud service provider in the world. We report on the non-containerized and containerized execution with Docker, as well as present the cost per simulation in AWS. The results show that our neural simulation pipeline can reduce entry barriers to neural simulations, making them more practical and cost-effective.

Two new methods of computer simulation of synchrotron radiation nanofocusing with planar compound refractive lenses (PCRLs) are presented. The methods are based on the results of analytical theory. In contrast to previous works, the new methods take into account the PCRL aperture. It is especially important at high photon energies, when absorption is low and the calculations based on analytical theory, i.e. without taking into account the aperture, give incorrect results. A computer program was created and specific results were obtained for a silicon PCRL having an aperture of 50 µm, element length of 102 µm and minimum thickness of 2 µm. For an energy of 50 keV and number of elements 300, it focuses the beam to 31 nm size at a distance of one and a half times its length. Analysis of the calculation accuracy for the proposed methods is performed, as well as a demonstration of the capabilities of the computer program.

The specific binding of the ubiquitous ‘marker of self’ protein CD47 to the SIRPα protein anchored in the macrophage plasma membrane results in the inhibition of the engulfment of ‘self’ cells by macrophages and thus constitutes a key checkpoint of our innate immune system. Consequently, the CD47–SIRPα protein complex has been recognized as a potential therapeutic target in cancer and inflammation. Here, we introduce a lattice-based mesoscale model for the biomimetic system studied recently in fluorescence microscopy experiments where GFP-tagged CD47 proteins on giant plasma membrane vesicles bind to SIRPα proteins immobilized on a surface. Computer simulations of the lattice-based mesoscale model allow us to study the biomimetic system on multiple length scales, ranging from single nanometers to several micrometers and simultaneously keep track of single CD47–SIRPα binding and unbinding events. Our simulations not only reproduce data from the fluorescence microscopy experiments but also are consistent with results of several other experiments, which validates our numerical approach. In addition, our simulations yield quantitative predictions on the magnitude and range of effective, membrane-mediated attraction between CD47–SIRPα complexes. Such detailed information on CD47–SIRPα interactions cannot be obtained currently from experiments alone. Our simulation results thus extend the present understanding of cooperative effects in CD47–SIRPα interactions and may have an influence on the advancement of new cancer treatments.

The article describes a specific method of using innovative transverse systems of flat bar frames as structures forcing elastic shape transformations of nominally flat folded sheets into the forms of ruled shell roof coverings. An innovative method for parametric shaping these forms and arrangement of frames constituting structural systems of sheds with folded thin-walled roof coverings, taking account of the specificity of designing elastically transformed roof sheeting, was proposed. The proposed method for defining the loads of the considered frames supporting lower shelves of the folds of transformed roof sheeting, as loads distributed uniformly along the length of the upper chord of a roof frame girder, is also an innovative approach. The above unconventional premises result in the innovative topic of the research presented in terms of checking the impact of changing the shape of subsequent flat frames (intended for the construction of sheds roofed with the transformed sheeting) on the geometric and mechanical properties of the members of these frames. For the defined loads and the proposed parameterization of the frame forms, an innovative set of conditions was developed to optimize their performance, and then a theoretical analysis of the observed dependencies was carried out. This analysis was performed in an unconventional, novel way using section modules of the cross-sections of all members. The performed computer simulations confirmed the significance of changes in the inclination of girders and columns on the geometric and mechanical properties of the members. The obtained results are the basis and justification for simulations and tests in the scope of further modification of the form, loads, work, and methods of using various configurations of flat frames in constructions.

The structure and dynamics of copolymers of 2-hydroxyethyl methacrylate (HEMA) with 2-methacryloyloxyethyl phosphorylcholine (MPC) were studied by molecular dynamics simulations. In total, 20 systems were analyzed. They differed in numerical fractions of the MPC in the copolymer chain, equal to 0.26 and 0.74, in the sequence of mers, block and random, and the water content, from 0 to 60% by mass. HEMA side chains proved relatively rigid and stable in all considered configurations. MPC side chains, in contrast, were mobile and flexible. Water substantially influenced their dynamics. The copolymer swelling caused by water resulted in diffusion channels, pronounced in highly hydrated systems. Water in the hydrates existed in two states: those that bond to the polymer chain and the free one; the latter was similar to bulk water but with a lower self-diffusion coefficient. The results proved that molecular dynamics simulations could facilitate the preliminary selection of the polymer materials for specific purposes before their synthesis.

The article presents the results of numerical simulations of the new forging process of the aircraft bracket forging at different deformation rates related to the type of machine used: a hydraulic press, a screw press and a drop forging hammer. The billet of shaped preforms from AZ91 alloy with two different geometries was used for the process. It was assumed that forging a bracket from an unformed, shaped preform will have a positive effect on the kinematics of the flow and on the deformation capability of AZ91 magnesium alloy, and will reduce the number of operations necessary to obtain the correct item. The numerical analysis of the new process was carried out with FEM, using the software Deform 3D. Based on the simulation, the important information about the process was obtained, that is the distribution of stress, deformation, temperatures, cracking and force parameters. The obtained results of numerical tests confirmed the possibility of producing the correct aircraft brackets forgings from AZ91 magnesium alloys with the proposed technology.

Respiration is one of the difficult biology topics, and teachers have challenges effectively teaching it to minimise misconceptions. The aims of this study was to analyse the effect of guided inquiry computer simulations on pre-service teachers' performance. A quasi-experimental design was used in this study. The subject in this study involving 65 in-service teachers, consist of 33 experimental groups taught using guided inquiry computer simulations, and 32 control groups received instructions using traditional chalk-and-talk. Data were collected using the Academic Performance Test and analysed using a T-test to determine the differences between the groups. Analysis of Covariance was used to find out the effect of the intervention. Both groups were pre-tested to gauge their previous knowledge and post-tested to establish changes after the teaching. The results show experimental group surpassed the control group. Also, males and females performance in the experimental group was similar, suggesting that guided inquiry computer simulations favoured both genders. It implies that guided inquiry computer simulations are effective tools to minimise misconceptions regarding cellular respiration. Thus, the researchers recommend using guided inquiry computer simulations in qualitative and quantitative approaches with a large sample of in-service teachers from different geographic regions.

Bisphenol A (BPA) is an endocrine-disrupting compound, and the binding mechanism of BPA with carrier proteins has drawn widespread attention. Halogen substitutions can significantly impact the properties of BPA, resulting in various effects for human health. Here, we selected tetrabromobisphenol A (TBBPA) and tetrachlorobisphenol A (TCBPA) to investigate the interaction between different halogen-substituted BPAs and human serum albumin (HSA). TBBPA/TCBPA spontaneously occupied site I and formed stable binary complexes with HSA. Compared to TCBPA, TBBPA has higher binding affinity to HSA. The effect of different halogen substituents on the negatively charged surface area of BPA was an important reason for the higher binding affinity of TBBPA to HSA compared to TCBPA. Hydrogen bonds and van der Waals forces were crucial in the TCBPA–HSA complex, while the main driving factor for the formation of the TBBPA–HSA complex was hydrophobic interactions. Moreover, the presence of TBBPA/TCBPA changed the secondary structure of HSA. Amino acid residues such as Lys199, Lys195, Phe211, Arg218, His242, Leu481, and Trp214 were found to play crucial roles in the binding process between BPA compounds and HSA. Furthermore, the presence of halogen substituents facilitated the binding of BPA compounds with HSA.

With the advancement in computational approaches and experimental, simulation, and modeling tools in recent decades, a trial-and-validation method is attracting more attention in the materials community. The development of powder metallurgy Ni-based superalloys is a vivid example that relies on simulation and experiments to produce desired microstructure and properties in a tightly controlled manner. In this research, we show an integrated approach to predicting the grain size of industrial forgings starting from lab-scale cylindrical compression by employing modeling and experimental validation. (a) Cylindrical compression tests to obtain accurate flow stress data and the hot working processing window; (b) double-cone tests of laboratory scale validation; (c) sub-scale forgings for further validation under production conditions; and (d) application and validation on full-scale industrial forgings. The procedure uses modeling and simulation to predict metal flow, strain, strain rate, temperature, and the resulting grain size as a function of thermo-mechanical processing conditions. The models are calibrated with experimental data until the accuracy of the modeling predictions is at an acceptable level, which is defined as the accuracy at which the results can be used to design and evaluate industrial forgings.

Variable-order fractional discrete calculus is a new and unexplored part of calculus that provides extraordinary capabilities for simulating multidisciplinary processes. Recognizing this incredible potential, the scientific community has been researching variable-order fractional discrete calculus applications to the modeling of engineering and physical systems. This research makes a contribution to the topic by describing and establishing the first generalized discrete fractional variable order Gronwall inequality that we employ to examine the finite time stability of nonlinear Nabla fractional variable-order discrete neural networks. This is followed by a specific version of a generalized variable-order fractional discrete Gronwall inequality described using discrete Mittag–Leffler functions. A specific version of a generalized variable-order fractional discrete Gronwall inequality represented using discrete Mittag–Leffler functions is shown. As an application, utilizing the contracting mapping principle and inequality approaches, sufficient conditions are developed to assure the existence, uniqueness, and finite-time stability of the equilibrium point of the suggested neural networks. Numerical examples, as well as simulations, are provided to show how the key findings can be applied.

Mathematical modelling and software simulation nowadays are very effective tools for both understanding and predicting corrosion processes and the protection of metallic components. COMSOL Multiphysics 5.6 software provides validated mathematical models that can be used, for a given geometry, as a tool to predict and prevent corrosion of components. The corrosion of zinc-coated steel sheets has been studied in this work by comparing results of the simulations with laboratory tests carried out in a salt spray. Results of both the mathematical modelling and empirical tests give the possibility to estimate the stability of the protective zinc layer over time. The examination of the discrepancies between two analytical methods for the investigation of corrosion phenomena leads to possible modifications in the model in order to reach as much as possible coherence with experimental data. As a final result, a computational model of corrosion phenomena in an automotive component has been reached, allowing in the future to partially substitute laboratory tests, usually being highly time consuming and expensive.

Water is an ubiquitous liquid that has several exotic and anomalous properties. Despite its apparent simple chemical formula, its capability of forming a dynamic network of hydrogen bonds leads to a rich variety of physics. Here we study the vibrations of water using molecular dynamics simulations, mainly concentrating on the Raman and infrared spectroscopic signatures. We investigate the consequences of the temperature on the vibrational frequencies, and we enter the details of the hydrogen bonding coordination by using restrained simulations in order to gain quantitative insight on the dependence of the frequencies on the neighbouring molecules. Further we consider the differences due to the different methods of solving the electronic structure to evaluate the forces on the ions, and report results on the angular correlations, isotopic mixtures HOD in H_2O/D_2O and and the dielectric constants in water.

Background: Selective targeting of malignant cells is the ultimate goal of anticancer studies around the world. There are some modalities for cancer therapy devastating tumor size and growth rate, meanwhile attacking normal cells. Utilizing appropriate ligands, like folate, allow the delivery of therapeutic molecules to cancer cells selectively. There are a variety of photosensitizers, like gold nanorods (GNRs), capable of absorbing the energy of light and converting it to heat, evidently build a photothermal procedure for cancer therapy.Objective: To develop a one-step approach for calculating the temperature distribution by solving the heat transfer equation with multiple heat sources originating from NIR laser-exposed GNRs. Material and Methods: In this experimental study, we simulated NIR laser heating process in a single cancer cell, with and without incubation with folate conjugated PEG-GNRs. This simulation was based on a real TEM image from an experiment with the same setup. An in vitro experiment based on aforesaid scenario was performed to validate the simulated model in practice. Results: According to the simplifications due to computational resource limits, the resulting outcome of simulation showed significant compatibility to the supporting experiment. Both simulation and experimental studies showed a similar trend for heating and cooling of the cells incubated with GNRs and irradiated by NIR laser (5 min, 1.8 W/cm2). It was observed that temperature of the cells in microplate reached 53.6 °C when irradiated by laser. Conclusion: This new method can be of great application in developing a planning technique for treating tumors utilizing GNP-mediated thermal therapy.

Abstract Caves and other subterranean habitats fulfill the requirements of experimental model systems to address general questions in ecology and evolution. Yet, the harsh working conditions of these environments and the uniqueness of the subterranean organisms have challenged most attempts to pursuit standardized research. Two main obstacles have synergistically hampered previous attempts. First, there is a habitat impediment related to the objective difficulties of exploring subterranean habitats and our inability to access the network of fissures that represents the elective habitat for the so‐called “cave species.” Second, there is a biological impediment illustrated by the rarity of most subterranean species and their low physiological tolerance, often limiting sample size and complicating laboratory experiments. We explore the advantages and disadvantages of four general experimental setups (in situ, quasi in situ, ex situ, and in silico) in the light of habitat and biological impediments. We also discuss the potential of indirect approaches to research. Furthermore, using bibliometric data, we provide a quantitative overview of the model organisms that scientists have exploited in the study of subterranean life. Our over‐arching goal is to promote caves as model systems where one can perform standardized scientific research. This is important not only to achieve an in‐depth understanding of the functioning of subterranean ecosystems but also to fully exploit their long‐discussed potential in addressing general scientific questions with implications beyond the boundaries of this discipline.

Respiration is one of the difficult biology topics, and teachers have challenges effectively teaching it to minimise misconceptions. The aims of this study was to analyse the effect of guided inquiry computer simulations on pre-service teachers' performance. A quasi-experimental design was used with 65 in-service teachers: 33 experimental groups taught using guided inquiry computer simulations, and 32 control groups received instructions using traditional chalk-and-talk. Data were collected using the Academic Performance Test and analysed using a T-test to determine the differences between the groups. Analysis of Covariance was used to find out the effect of the intervention. Both groups were pre-tested to gauge their previous knowledge and post-tested to establish changes after the teaching. The results show experimental group surpassed the control group. Also, males and females performance in the experimental group was similar, suggesting that guided inquiry computer simulations favoured both genders. It implies that guided inquiry computer simulations are effective tools to minimise misconceptions regarding cellular respiration. Thus, the researchers recommend using guided inquiry computer simulations in qualitative and quantitative approaches with a large sample of in-service teachers from different geographic regions.

Conjugative plasmids often carry virulence and antibiotic-resistant genes. Therefore, understanding the behavior of these extra-chromosomal DNA elements gives insights into their spread. Bacteria frequently replicate slower after plasmids’ entry, an observation inconsistent with the plasmids’ ubiquity in nature. Several hypotheses explain the maintenance of plasmids among bacterial communities. However, the numerous combinations of bacterial species and strains, plasmids, and environments claim a robust elucidatory mechanism of plasmid maintenance. Previous works have shown that donor cells already adapted to the plasmid may use the plasmid as a ‘weapon’ to compete with non-adapted plasmid-free cells. Computer simulations corroborated this hypothesis with a wide range of parameters. Here we show that donor cells benefit from harboring conjugative plasmids even if compensatory mutations in transconjugant cells occur in the plasmid, not on chromosomes. The advantage’s leading causes are as follows: mutations take time to appear, many plasmids remain costly, and re-transfer of mutated plasmids usually occurs in sites distant to the original donors, implying little competition between these cells. Research in previous decades cautioned against uncritical acceptance of the hypothesis that resistance cost helps to preserve antibiotics’ effectiveness. This work gives a new twist to this conclusion by showing that costs help antibiotic-resistant bacteria to compete with plasmid-free cells even if compensatory mutations appear in plasmids.

The pacemaker activity of the sinoatrial node (SAN) has been studied extensively in animal species but is virtually unexplored in humans. Here we assess the role of the slowly activating component of the delayed rectifier K+ current (IKs) in human SAN pacemaker activity and its dependence on heart rate and β-adrenergic stimulation. HEK-293 cells were transiently transfected with wild-type KCNQ1 and KCNE1 cDNA, encoding the α- and β-subunits of the IKs channel, respectively. KCNQ1/KCNE1 currents were recorded both during a traditional voltage clamp and during an action potential (AP) clamp with human SAN-like APs. Forskolin (10 µmol/L) was used to increase the intracellular cAMP level, thus mimicking β-adrenergic stimulation. The experimentally observed effects were evaluated in the Fabbri–Severi computer model of an isolated human SAN cell. Transfected HEK-293 cells displayed large IKs-like outward currents in response to depolarizing voltage clamp steps. Forskolin significantly increased the current density and significantly shifted the half-maximal activation voltage towards more negative potentials. Furthermore, forskolin significantly accelerated activation without affecting the rate of deactivation. During an AP clamp, the KCNQ1/KCNE1 current was substantial during the AP phase, but relatively small during diastolic depolarization. In the presence of forskolin, the KCNQ1/KCNE1 current during both the AP phase and diastolic depolarization increased, resulting in a clearly active KCNQ1/KCNE1 current during diastolic depolarization, particularly at shorter cycle lengths. Computer simulations demonstrated that IKs reduces the intrinsic beating rate through its slowing effect on diastolic depolarization at all levels of autonomic tone and that gain-of-function mutations in KCNQ1 may exert a marked bradycardic effect during vagal tone. In conclusion, IKs is active during human SAN pacemaker activity and has a strong dependence on heart rate and cAMP level, with a prominent role at all levels of autonomic tone.

The results of a computer simulation of laser beams focused by a combined multichannel array system in the atmosphere are presented. Beam propagation on atmospheric paths is considered taking into account the influence of turbulence and time-dependent thermal blooming interactions. The increase in the maximum intensity of the focal spot due to the optimization of the initial power density of the emitting aperture is estimated. It is shown that the scaling of the optimal initial power in multichannel arrays preserves the proportional dependence of the maximum intensity in focus with an increase in the number of channels. For wave-optics simulation, custom made software was developed based on the split-step method and modified for parallel algorithms using the functions of the Intel ® Math Kernel Library.

Today, computer-based simulations are widely used in a range of industries and fields for various purposes. They are helpful in testing different scenarios and hypotheses, allowing users to explore the consequences of different decisions and actions. This study aimed to explore the university students’ attitudes and experiences of using simulations to facilitate their unsupervised (without teachers’ support) learning of science concepts. This study involved 566 university students who used online simulations so support their unsupervised learning of science content in physics, chemistry, math, earth science, and biology. The data collected via a cross-sectional survey were analyzed using parametric statistics. The participants of the study showed a high -level of engagement and satisfaction with the use of simulations for unsupervised science learning, suggesting that computer-based simulations have the potential to serve as a user-centered learning interface capable of engaging university students without the teachers’ support. This study did not find a gender-based divide in the students’ experiences. Participants’ independent learning abilities were found to have a significant positive influence on their satisfaction and engagement. The results of this study have theoretical and practical implications for science learning beyond classroom walls.

The crystallization of materials from a suspension determines the structure and function of the final product, and numerous pieces of evidence have pointed out that the classical crystallization pathway may not capture the whole picture of the crystallization pathways. However, visualizing the initial nucleation and further growth of a crystal at the nanoscale has been challenging due to the difficulties of imaging individual atoms or nanoparticles during the crystallization process in solution. Recent progress in nanoscale microscopy had tackled this problem by monitoring the dynamic structural evolution of crystallization in a liquid environment. In this review, we summarized several crystallization pathways captured by the liquid-phase transmission electron microscopy technique and compared the observations with computer simulation. Apart from the classical nucleation pathway, we highlight three nonclassical pathways that are both observed in experiments and computer simulations: formation of an amorphous cluster below the critical nucleus size, nucleation of the crystalline phase from an amorphous intermediate, and transition between multiple crystalline structures before achieving the final product. Among these pathways, we also highlight the similarities and differences between the experimental results of the crystallization of single nanocrystals from atoms and the assembly of a colloidal superlattice from a large number of colloidal nanoparticles. By comparing the experimental results with computer simulations, we point out the importance of theory and simulation in developing a mechanistic approach to facilitate the understanding of the crystallization pathway in experimental systems. We also discuss the challenges and future perspectives for investigating the crystallization pathways at the nanoscale with the development of in situ nanoscale imaging techniques and potential applications to the understanding of biomineralization and protein self-assembly.

The computer simulations are considered as the required tool to design the suitable autonomous control systems optimal in different senses and especially in providing the restrictions of the jerk motions for the robotic wheeled platforms. The subject matter of this research is the development of the theory and methods for computer simulations of the controllability processes of the robotic wheeled platforms. The goal of this research is to consider the jerks of the wheeled platforms, and the jerks are reduced to the limitation of the acceleration time derivative of the mass center of the wheeled platform, so that this derivative is considered as the quantitative estimation of the jerks. The incorrectness in the Hadamard's sense for direct defining the jerks by differentiations of the phase coordinates in the case of computer simulations using the numerical methods is discussed. Tasks of this research are in developing the generalized approaches for mathematical modelling and computer simulations and in theoretical receiving of the properties inherent for the wheeled platforms and suitable for verification the computer simulations results, as well as in making the calculations to have the quantitative results about the controllability processes for the particular case of the electromechanical four-wheeled platform under the straight motion with the mode of speeding-up from the state of the rest. Methods of this research are based on the Lagrange's equations of second kind, as well as on the electromechanical analogies, and on final representing the mathematical models in the form of the system of the first ordered ordinary differential equations with the initial conditions for further numerical solving. The computer simulations are accomplished by using the Scilab free open source software. Results of this research are in the proposed suitable way for computing the jerks by the phase coordinates without its differentiations allow excluding the incorrectness in the Hadamard's sense, as well as in representing the controllability processes for the electromechanical wheeled platform, including the results for the velocities, the accelerations and the jerks which are necessary to illustrate the controllability processes for the robotic wheeled platforms. By comparison with the theoretically established inherent properties of the wheeled platforms it is shown the correctness of the results of the computer simulations. Conclusions about this research are that the developed approaches for computer simulations of the controllability processes for the robotic wheeled platforms allow considering influence of the control on the different characteristics including the velocity, the acceleration, as well as the jerk motions which are required for designing the controls optimal in different senses.

A short experimental activity aimed at upper level undergraduate students or beginner researchers is presented to introduce the concepts of edge effects and hemispherical diffusion at ultramicroelectrodes. Students will perform simple cyclic voltammetry experiments varying the scan rate and using disk electrodes with different radii. They are then asked to interpret the results based on their previous knowledge. Simulations are also performed, which provide a clear visual interpretation of the underlying diffusion process and show the transition between linear and hemispherical diffusion regimes. The simulations are also presented as a tool to extend the study beyond the range of experimentally accessible conditions. The interplay between voltammetry experiments and simulations allows a natural comprehension of these concepts without the need of a previous rigorous theoretical introduction.

Electroencephalography is the recording of brain electrical activities that can be used to diagnose brain seizure disorders. By identifying brain activity patterns and their correspondence between symptoms and diseases, it is possible to give an accurate diagnosis and appropriate drug therapy to patients. This work aims to categorize electroencephalography signals on different channels' recordings for classifying and predicting epileptic seizures. The collection of the electroencephalography recordings contained in the dataset attributes 179 information and 11,500 instances. Instances are of five categories, where one is the symptoms of epilepsy seizure. We have used traditional, ensemble methods and deep machine learning techniques highlighting their performance for the epilepsy seizure detection task. One dimensional convolutional neural network, ensemble machine learning techniques like bagging, boosting (AdaBoost, gradient boosting, and XG boosting), and stacking is implemented. Traditional machine learning techniques such as decision tree, random forest, extra tree, ridge classifier, logistic regression, K-Nearest Neighbor, Naive Bayes (gaussian), and Kernel Support Vector Machine (polynomial, gaussian) are used for classifying and predicting epilepsy seizure. Before using ensemble and traditional techniques, we have preprocessed the data set using the Karl Pearson coefficient of correlation to eliminate irrelevant attributes. Further accuracy of classification and prediction of the classifiers are manipulated using k-fold cross-validation methods and represent the Receiver Operating Characteristic Area Under the Curve for each classifier. After sorting and comparing algorithms, we have found the convolutional neural network and extra tree bagging classifiers to have better performance than all other ensemble and traditional classifiers.

One of important tasks in a development of gas-condensate fields is to minimize hydrocarbons loss arising from the gas condensation in pores of the gas-bearing layer. The search for the optimal gas production regime is carried out both on the basis of laboratory experiments and on the base of computer simulation. In this regard, the relevant is the verification of the constructed mathematical models by means of comparison of numerical results with experimental data obtained on the laboratory models of a hydrocarbon reservoirs. Within the classical approach on the basis of the Darcy law and the law continuity for flows, the model is formulated that describes the passing a multicomponent gas-condensate mixture through a porous medium in the depletion mode. The numerical solution of the corresponding system of nonlinear partial differential equations is implemented on the basis of the combined use of the C++ programming language and the Maple software. Shown that the approach used provides an agreement of results of numerical simulations with experimental data on the dynamics of hydrocarbon recoverability depending on the pressure obtained at VNIIGAZ, Ukhta.

The article presents the results of research on the range of the impact of a cooling facility on the surrounding ground. An analysis of the heat exchange with the ground and through the building partitions was carried out. The analysis was carried out on the basis of the results of actual field tests carried out throughout the measurement year. The object of the research was an agricultural cold store located in southern Poland. The computational analysis of the interaction between the cooling facility and the ground was based on the numerical elementary balances method. The validation of the calculation model was performed based on the adopted boundary conditions. Calculations for the analyzed variants were carried out on the basis of a geometric model of the cooling facility built in the WUFI®plus program, corresponding to the actual dimensions. The analysis of the energy balance of the studied facility showed that the share of energy flow through the floor to the ground constitutes 8.2% of all energy flows through other partitions and the ventilation system. In order to maintain the set air temperature inside the studied building, intensive cooling was required with an energy demand of 5184.5 kWh/year. The results of the research showed that the range of the thermal impact of the building changes depending on the location of the studied ground area in terms of cardinal direction. The external and internal microclimate characteristics also affect the extent of the impact of the cooling facility on the surrounding ground. Under the assumption of stable values of Θi within a range of 0.0–4.0 °C, the largest range of influence (4.0 m) occurs in the summer.