Computational Model Research Articles

Impact of interventions to reduce nosocomial transmission of SARS-CoV-2 in English NHS Trusts: a computational modelling study

BackgroundPrior to September 2021, 55,000–90,000 hospital inpatients in England were identified as having a potentially nosocomial SARS-CoV-2 infection. This includes cases that were likely missed due to pauci- or asymptomatic infection. Further, high numbers of healthcare workers (HCWs) are thought to have been infected, and there is evidence that some of these cases may also have been nosocomially linked, with both HCW to HCW and patient to HCW transmission being reported. From the start of the SARS-CoV-2 pandemic interventions in hospitals such as testing patients on admission and universal mask wearing were introduced to stop spread within and between patient and HCW populations, the effectiveness of which are largely unknown.Materials/methodsUsing an individual-based model of within-hospital transmission, we estimated the contribution of individual interventions (together and in combination) to the effectiveness of the overall package of interventions implemented in English hospitals during the COVID-19 pandemic. A panel of experts in infection prevention and control informed intervention choice and helped ensure the model reflected implementation in practice. Model parameters and associated uncertainty were derived using national and local data, literature review and formal elicitation of expert opinion. We simulated scenarios to explore how many nosocomial infections might have been seen in patients and HCWs if interventions had not been implemented. We simulated the time period from March-2020 to July-2022 encompassing different strains and multiple doses of vaccination.ResultsModelling results suggest that in a scenario without inpatient testing, infection prevention and control measures, and reductions in occupancy and visitors, the number of patients developing a nosocomial SARS-CoV-2 infection could have been twice as high over the course of the pandemic, and over 600,000 HCWs could have been infected in the first wave alone. Isolation of symptomatic HCWs and universal masking by HCWs were the most effective interventions for preventing infections in both patient and HCW populations. Model findings suggest that collectively the interventions introduced over the SARS-CoV-2 pandemic in England averted 400,000 (240,000 – 500,000) infections in inpatients and 410,000 (370,000 – 450,000) HCW infections.ConclusionsInterventions to reduce the spread of nosocomial infections have varying impact, but the package of interventions implemented in England significantly reduced nosocomial transmission to both patients and HCWs over the SARS-CoV-2 pandemic.

Method for expert evaluation of the technical con-dition of the cylinder-piston group of automotive engines after hydrolock

Problem: The study examines the thermogasdynamic process within an internal combustion engine cylinder during cold cranking mode while measuring compression. Analysis of various models and comparison of known data revealed unresolved challenges in constructing mathematical models of the engine operating cycle. The vast majority of practical data and recommendations for compression measurement in a cylinder are based on empirical knowledge, numerous experiments, and tests. Consequently, there arises a need for computational models of the compression measurement process and their theoretical justification, particularly in cases where engine damage occurs during hydrolock in a cylinder. Methodology. To address the identified issues, a mathematical model of the thermogasdynamic process within the cylinder during cold cranking while measuring compression was developed. Originality. Unlike existing models, this model describes the processes in the cylinder step by step, considering the real nature of intake-exhaust processes, air leakage through part interfaces, and heat exchange with the walls. Through modeling, the main patterns of compression changes depending on the modes and the nature of damage to associated parts of the valve mechanism and the cylinder-piston group were identified, including deformation of the connecting rod during hydraulic lock due to liquid entering the cylinder. Practical value. Based on the study results, it was concluded that the model's properties make it effectively applicable in diagnosing and monitoring the technical condition of automotive engines during operation.

Large environmental changes reduce valence-dependent belief updating

When updating beliefs, humans tend to integrate more desirable information than undesirable information. In stable environments (low uncertainty and high predictability), this asymmetry favors motivation towards action and perceived self-efficacy. However, in changing environments (high uncertainty and low predictability), this process can lead to risk underestimation and increase unwanted costs. Here, we examine how people (n = 388) integrate threatening information during an abrupt environmental change (mandatory quarantine during the COVID-19 pandemic). Given that anxiety levels are associated with the magnitude of the updating belief asymmetry; we explore its relationship during this particular context. We report a significant reduction in asymmetrical belief updating during a large environmental change as individuals integrated desirable and undesirable information to the same extent. Moreover, this result was supported by computational modeling of the belief update task. However, we found that the reduction in asymmetrical belief updating was not homogeneous among people with different levels of Trait-anxiety. Individuals with higher levels of Trait-anxiety maintained a valence-dependent updating, as it occurs in stable environments. On the other hand, updating behavior was not associated with acute anxiety (State-Anxiety), health concerns (Health-Anxiety), or having positive expectations (Trait-Optimism). These results suggest that highly uncertain environments can generate adaptive changes in information integration. At the same time, it reveals the vulnerabilities of individuals with higher levels of anxiety to adapt the way they learn.

Nested structure role in the mechanical response of spicule inspired fibers.

Euplectella aspergillum marine sponge spicules are renowned for their remarkable strength and toughness. These spicules exhibit a unique concentric layering structure, which contributes to their exceptional mechanical resistance. In this study, finite element method simulations were used to comprehensively investigate the effect of nested cylindrical structures on the mechanical properties of spicules. This investigation leveraged scanning electron microscopy images to guide the computational modeling of the microstructure and the results were validated by three-point bending tests of 3D-printed spicule-inspired structures. The numerical analyses showed that the nested structure of spicules induces stress and strain jumps on the layer interfaces, reducing the load on critical zones of the fiber and increasing its toughness. It was found that this effect shows a tapering enhancement as the number of layers increases, which combines with a threshold related to the 3D-printing manufacturability to suggest a compromise for optimal performance. A comprehensive evaluation of the mechanical properties of these fibers can assist in developing a new generation of bioinspired structures with practical real-world applications.

A general neural membrane computing model

Neural P systems are a class of distributed parallel computing models inspired by the way neurons cooperate in biological neural networks. Artificial neural networks integrate biological neural networks with mathematical models, which have powerful information processing capabilities. This work adopts the structure and data processing method of neural networks and integrates them with membrane computing to improve the neural P systems in data processing. A general neural membrane computing (GNMC) model is developed to realize the flow and manipulation of data in the form of objects and rules in the neuron. Glial cells are introduced into the GNMC model at the cellular level to modulate the states of the connected neurons. The trigger conditions, the activation mechanisms and the dissolve-reconnect rules make the GNMC model more efficient in handling objects. The multiple objects and multiple topological structures enable the GNMC model to handle different practical problems. The Turing universality of the GNMC model is proved as number generating and accepting devices. Furthermore, a small universal GNMC model with 71 neurons, fewer than that of the existing state-of-the-art neural P systems, is constructed for computing functions.

Bayesian uncertainty evaluation applied to the tilted-wave interferometer

The tilted-wave interferometer is a promising technique for the development of a reference measurement system for the highly accurate form measurement of aspheres and freeform surfaces. The technique combines interferometric measurements, acquired with a special setup, and sophisticated mathematical evaluation procedures. To determine the form of the surface under test, a computational model is required that closely mimics the measurement process of the physical measurement instruments. The parameters of the computational model, comprising the surface under test sought, are then tuned by solving an inverse problem. Due to this embedded structure of the real experiment and computational model and the overall complexity, a thorough uncertainty evaluation is challenging. In this work, a Bayesian approach is proposed to tackle the inverse problem, based on a statistical model derived from the computational model of the tilted-wave interferometer. Such a procedure naturally allows for uncertainty quantification to be made. We present an approximate inference scheme to efficiently sample quantities of the posterior using Monte Carlo sampling involving the statistical model. In particular, the methodology derived is applied to the tilted-wave interferometer to obtain an estimate and corresponding uncertainty of the pixel-by-pixel form of the surface under test for two typical surfaces taking into account a number of key influencing factors. A statistical analysis using experimental design is employed to identify main influencing factors and a subsequent analysis confirms the efficacy of the method derived.

Application of digital twins for simulation based tailoring of laser induced graphene

In the era of man–machine interfaces, digital twins stand as a key technology, offering virtual representations of real-world objects, processes, and systems through computational models. They enable novel ways of interacting with, comprehending, and manipulating real-world entities within a virtual realm. The real implementation of graphene-based sensors and electronic devices remains challenging due to the integration complexities of high-quality graphene materials with existing manufacturing processes. To address this, scalable techniques for the in-situ fabrication of graphene-like materials are essential. One promising method involves using a CO2 laser to convert polyimide into graphene. Optimizing this graphitization process is hindered by complex parameter interactions and nonlinear terms. This article explores how these digital replicas can enhance the fabrication of laser-induced graphene (LIG) through laser simulation and machine learning methods to enable rapid single-step LIG patterning. This approach aims to create a universal simulation for all CO2 lasers, calculating optical energy flux and utilizing machine learning to control and predict LIG conductivity (ability to conduct current), morphology, and electrical resistance. The proposed procedure, integrating digital twins in the LIG production process, will avoid or reduce the preliminary tests required to determine the proper laser parameters to reach the desired LIG characteristics. Accordingly, this approach will reduce the time and costs associated with these tests and thus increase the efficiency and optimize the procedure.

Identification and characterization of a new potent inhibitor targeting CtBP1/BARS in melanoma cells

BackgroundThe C-terminal-binding protein 1/brefeldin A ADP-ribosylation substrate (CtBP1/BARS) acts both as an oncogenic transcriptional co-repressor and as a fission inducing protein required for membrane trafficking and Golgi complex partitioning during mitosis, hence for mitotic entry. CtBP1/BARS overexpression, in multiple cancers, has pro-tumorigenic functions regulating gene networks associated with “cancer hallmarks” and malignant behavior including: increased cell survival, proliferation, migration/invasion, epithelial-mesenchymal transition (EMT).Structurally, CtBP1/BARS belongs to the hydroxyacid-dehydrogenase family and possesses a NAD(H)-binding Rossmann fold, which, depending on ligands bound, controls the oligomerization of CtBP1/BARS and, in turn, its cellular functions.Here, we proposed to target the CtBP1/BARS Rossmann fold with small molecules as selective inhibitors of mitotic entry and pro-tumoral transcriptional activities.MethodsStructured-based screening of drug databases at different development stages was applied to discover novel ligands targeting the Rossmann fold. Among these identified ligands, N-(3,4-dichlorophenyl)-4-{[(4-nitrophenyl)carbamoyl]amino}benzenesulfonamide, called Comp.11, was selected for further analysis. Fluorescence spectroscopy, isothermal calorimetry, computational modelling and site-directed mutagenesis were employed to define the binding of Comp.11 to the Rossmann fold. Effects of Comp.11 on the oligomerization state, protein partners binding and pro-tumoral activities were evaluated by size-exclusion chromatography, pull-down, membrane transport and mitotic entry assays, Flow cytometry, quantitative real-time PCR, motility/invasion, and colony assays in A375MM and B16F10 melanoma cell lines. Effects of Comp.11 on tumor growth in vivo were analyzed in mouse tumor model.ResultsWe identify Comp.11 as a new, potent and selective inhibitor of CtBP1/BARS (but not CtBP2). Comp.11 directly binds to the CtBP1/BARS Rossmann fold affecting the oligomerization state of the protein (unlike other known CtBPs inhibitors), which, in turn, hinders interactions with relevant partners, resulting in the inhibition of both CtBP1/BARS cellular functions: i) membrane fission, with block of mitotic entry and cellular secretion; and ii) transcriptional pro-tumoral effects with significantly hampered proliferation, EMT, migration/invasion, and colony-forming capabilities. The combination of these effects impairs melanoma tumor growth in mouse models. ConclusionsThis study identifies a potent and selective inhibitor of CtBP1/BARS active in cellular and melanoma animal models revealing new opportunities to study the role of CtBP1/BARS in tumor biology and to develop novel melanoma treatments.

Estimation of Multiple Contact Conductances in a Silicon-Indium-Silicon Stack

Abstract This report documents evaluation of simultaneous estimation of multiple interfacial heat transfer coefficients (HTCs) using transient measurements from an experiment designed for steady-state operation. The design of a mirror system for directing x-rays under cryogenic conditions requires knowledge of the interfacial HTC (contact conductance) between silicon and indium. An experimental apparatus was constructed to measure temperatures in a stack of five 7.62 mm thick pucks of silicon separated by 0.1 mm thick sheets of indium which is operated under cryogenic temperatures in vacuum. Multiple pucks and interfaces are incorporated into the apparatus to allow evaluation of HTCs for surfaces of different roughness from a single experiment. Analysis of the sensitivity of each of the measured temperatures to each of the unknown HTCs reveals lack of linear independence of these sensitivities and suggests the recovery of the HTCs will be challenging. Artificially noised “data” were created from two different computational models by solving for temperatures and adding random Gaussian noise with a specified standard deviation. These data are subsequently analyzed using two different iterative parameter estimation methods: a Levenberg scheme and a Tikhonov iterative scheme. The required sensitivity matrix is computed using forward finite difference approximations. The results for the heat transfer coefficients for this model problem suggest that coefficients cannot be estimated independently, but the ratios relative to one of the unknowns can be recovered.

Advanced thermoconversion technology for municipal solid waste energetic valorization

This paper presents a novel approach to tackle the dual challenges of energy scarcity and municipal solid waste management by exploiting the potential of municipal solid waste gasification. The performance of the modified updraft gasifier is evaluated using computational modeling with Aspen Plus V14 software. The reliability of the gasification model is confirmed by comparing it with experimental data, highlighting its accuracy in estimating key gas composition parameters. A detailed analysis of the percentage error between the gas's experimentally measured lower heating value and the model-estimated value is performed. Results show a 12.2 % error for municipal solid waste gasification, meaning the experimental lower heating value is higher than the model's estimation. On the other hand, a 27,2 % error is observed for pellet gasification, implying a lower experimental lower heating value than the model's estimation. These findings provide useful information for future optimization and improvement of the gasification process, further advancing the field of waste-to-energy conversion and promoting sustainable energy generation.

Seismic Domain Identification Algorithm Using Fuzzy Logic Methods With Combined Geological and Geomorphological Data for the Case of Sakhalin Island

Seismic Domain Identification Algorithm Using Fuzzy Logic Methods With Combined Geological and Geomorphological Data for the Case of Sakhalin Island

The effect of the pitch of the boards in the transverse layer on the deformability and stress distribution in a threelayer CLT panel rigidly clamped on both sides

CLT panels are made by gluing several layers of boards crosswise, which provides them with high load-bearing capacity and bending resistance. In addition to the number of layers in the panel, the deformability and bearing capacity are influenced by the geometric parameters of the plate, the way the layers are attached to each other, the way the structure is supported, etc. Due to the fact that the material has recently been used in construction, many issues remain poorly understood, and therefore there is an opportunity and need to optimize some aspects both in the CLT panels themselves and in the way they interact with other building structures.In this article, the influence of the pitch of boards in the transverse layer on the deformability and stress distribution in a three-layer CLT panel rigidly pinched on both sides was studied. Numerical studies of the finite element method (FEM) were carried out using the computing complex SCAD+. The computational model of the plate in this study is a composite orthotropic plate with rigid connections between the layers. The result of the study is numerical data reflecting the dependence of the distribution of normal stresses OX and OY and the transverse deformation of the plate on the pitch of the lamellae (boards) in the bottom layer. Projections of the computational model with normal stress isofields on the stretched and compressed plate layer are also obtained. This makes it possible to identify general patterns of stress distribution and deformation changes with variations in geometric parameters for this type of support for their use in the design of building structures using CLT panels as well as in the optimization of the structure in order to increase the cost efficiency of resources.

Computational investigations of Ka-226T helicopter coaxial rotor aerodynamics in the vortex ring state

The vortex ring states are observed when the rotor is flowed at positive angles of attack. For the main rotor, these conditions are realized during a steep descent of the helicopter at low speeds. The rotor vortex ring states are affected by significant phenomena related to the behavior of its aerodynamics, including negative phenomena. The latter is, firstly, referred to decrease in rotor thrust, increase in the required power, pulsations of thrust and torque, unsteady flapping blade motion, etc. In terms of helicopter piloting, it means a sharp loss of altitude, increase in the control force, a high level of vibration, defocusing attenuation of rotor spinning cone, as well as controllability deterioration. All these factors determine the relevance of research on these modes and the importance of solving a problem of defining their boundaries. Recently, due to the rapid development of computer technologies and computational models, it has become practical to perform numerical research of the rotor aerodynamics in vortex ring states. The paper presents the study results of Ka-226T helicopter coaxial rotor aerodynamics in steep descent modes in the field of vortex ring states. The angles of rotor attack αВ = 90...30° and the range of vertical descent velocities Vу = 0...26 m/s are considered. The original nonlinear bladed vortex model of the rotor developed at the Moscow Aviation Institute (MAI) was used. The total and distributed aerodynamic rotor characteristics were calculated. The shapes of the vortex wake and the rotor flow patterns were analyzed. The boundaries of the vortex ring states in velocity coordinates “Vx − Vу” were constructed according to various criteria reflecting the known features of these states. The results obtained significantly complement the existing experience of experimental and numerical research in this field.

Removing direct photocurrent artifacts in optogenetic connectivity mapping data via constrained matrix factorization.

Monosynaptic connectivity mapping is crucial for building circuit-level models of neural computation. Two-photon optogenetic stimulation, when combined with whole-cell recording, enables large-scale mapping of physiological circuit parameters. In this experimental setup, recorded postsynaptic currents are used to infer the presence and strength of connections. For many cell types, nearby connections are those we expect to be strongest. However, when the postsynaptic cell expresses opsin, optical excitation of nearby cells can induce direct photocurrents in the postsynaptic cell. These photocurrent artifacts contaminate synaptic currents, making it difficult or impossible to probe connectivity for nearby cells. To overcome this problem, we developed a computational tool, Photocurrent Removal with Constraints (PhoRC). Our method is based on a constrained matrix factorization model which leverages the fact that photocurrent kinetics are less variable than those of synaptic currents. We demonstrate on real and simulated data that PhoRC consistently removes photocurrents while preserving synaptic currents, despite variations in photocurrent kinetics across datasets. Our method allows the discovery of synaptic connections which would have been otherwise obscured by photocurrent artifacts, and may thus reveal a more complete picture of synaptic connectivity. PhoRC runs faster than real time and is available as open source software.

The bioelectric mechanisms of local calcium dynamics in cancer cell proliferation: an extension of the A549 in silico cell model

The bioelectric mechanisms of local calcium dynamics in cancer cell proliferation: an extension of the A549 in silico cell model

A model with multiple intracranial aneurysms: possible hemodynamic mechanisms of aneurysmal initiation, rupture and recurrence

BackgroundHemodynamic factors play an important role in aneurysm initiation, growth, rupture, and recurrence, while the mechanism of the hemodynamic characteristics is still controversial. A unique model of multiple aneurysms (initiation, growth, rupture, and recurrence) is helpful to avoids the confounders and further explore the possible hemodynamic mechanisms of aneurysm in different states.MethodsWe present a model with multiple aneurysms, and including the states of initiation, growth, rupture, and recurrence, discuss the proposed mechanisms, and describe computational fluid dynamic model that was used to evaluate the likely hemodynamic effect of different states of the aneurysms.ResultsThe hemodynamic analysis suggests that high flow impingement and high WSS distribution at normal parent artery was found before aneurysmal initiation. The WSS distribution and flow velocity were decreased in the new sac after aneurysmal growth. Low WSS was the risk hemodynamic factor for aneurysmal rupture. High flow concentration region on the neck plane after coil embolization still marked in recanalized aneurysm.ConclusionsAssociations have been identified between high flow impingement and aneurysm recanalization, while low WSS is linked to the rupture of aneurysms. High flow concentration and high WSS distribution at normal artery associated with aneurysm initiation and growth, while after growth, the high-risk hemodynamics of aneurysm rupture was occurred, which is low WSS at aneurysm dome.

In-Depth Analysis of the Selection of PBPK Modeling Tools: Bibliometric and Social Network Analysis of the Open Systems Pharmacology Community.

Since the Open Source Initiative laid the foundation for the open source software environment in 1998, the popularity of free and open source software has been steadily increasing. Model-informed drug discovery and development (MID3), a key component of pharmaceutical research and development, heavily makes use of computational models which can be developed using various software including the Open Systems Pharmacology (OSP) software (PK-Sim/MoBi), a free and open source software tool for physiologically based pharmacokinetic (PBPK) modeling. In this study, we aimed to investigate the impact, application areas, and reach of the OSP software as well as the relationships and collaboration patterns between organizations having published OSP-related articles between 2017 and 2023. Therefore, we conducted a bibliometric analysis of OSP-related publications and a social network analysis of the organizations with which authors of OSP-related publications were affiliated. On several levels, we found evidence for a significant growth in the size of the OSP community as well as its visibility in the MID3 community since OSP's establishment in 2017. Specifically, the annual publication rate of PubMed-indexed PBPK-related articles using the OSP software outpaced that of PBPK-related articles using any software. Our bibliometric analysis and network analysis demonstrated that the expansion of the OSP community was predominantly driven by new authors and organizations without prior connections to the community involving the generation of research clusters de novo and an overall diversification of the network. These findings suggest an ongoing evolution of the OSP community toward a more segmented, diverse, and inclusive network.

Improvement of Perovskite Solar Cells Efficiency by Management of the Electron Withdrawing Groups in Hole Transport Materials: Theoretical Calculation and Experimental Verification.

Management of functional groups in hole transporting materials (HTMs) is a feasible strategy to improve perovskite solar cells (PSCs) efficiency. Therefore, starting from the carbazole-diphenylamine-based JY7 molecule, JY8 and JY9 molecules are incorporated into the different electron-withdrawing groups of fluorine and cyano groups on the side chains. The theoretical results reveal that the introduction of electron-withdrawing groups of JY8 and JY9 can improve these highest occupied molecular orbital(HOMO)energy levels, intermolecular stacking arrangements, and stronger interface adsorption on the perovskite. Especially, the results of molecular dynamics (MD) indicate that the fluorinated JY8 molecule can yield a preferred surface orientation, which exhibits stronger interface adsorption on the perovskite. To validate the computational model, the JY7-JY9 are synthesized and assembled into PSC devices. Experimental results confirm that the HTMs of JY8 exhibit outstanding performance, such as high hole mobility, low defect density, and efficient hole extraction. Consequently, the PSC devices based on JY8 achieve a higher PCE than those of JY7 and JY9. This work highlights the management of the electron-withdrawing groups in HTMs to realize the goal of designing HTMs for the improvement of PSC efficiency.

Tuning Two-Dimensional Phthalocyanine Dual Site Metal-Organic Framework Catalysts for the Oxygen Reduction Reaction.

Metal-organic frameworks (MOFs) offer an interesting opportunity for catalysis, particularly for metal-nitrogen-carbon (M-N-C) motifs by providing an organized porous structural pattern and well-defined active sites for the oxygen reduction reaction (ORR), a key need for hydrogen fuel cells and related sustainable energy technologies. In this work, we leverage electrochemical testing with computational models to study the electronic and structural properties in the MOF systems and their relationship to ORR activity and stability based on dual transitional metal centers. The MOFs consist of two M1 metals with amine nodes coordinated to a single M2 metal with a phthalocyanine linker, where M1/M2 = Co, Ni, or Cu. Co-based metal centers, in particular Ni-Co, demonstrate the highest overall activity of all nine tested MOFs. Computationally, we identify the dominance of Co sites, relative higher importance of the M2 site, and the role of layer M1 interactions on the ORR activity. Selectivity measurements indicate that M1 sites of MOFs, particularly Co, exhibit the lowest (<4%), and Ni demonstrates the highest (>46%) two-electron selectivity, in good agreement with computational studies. Direct in situ stability characterization, measuring dissolved metal ions, and calculations, using an alkaline stability metric, confirm that Co is the most stable metal in the MOF, while Cu exhibits notable instability at the M1. Overall, this study reveals how atomistic coupling of electronic and structural properties affects the ORR performance of dual site MOF catalysts and opens new avenues for the tunable design and future development of these systems for practical electrochemical applications.

Stiffness of reinforced concrete structures under bending considering shear and axial forces (part 2)

The paper presents a physical and computational model for determining the parameters of limit states of reinforced concrete structures under complex stressed state - bending with axial and shear forces. Based on the adopted scheme of cross-section discretization and A.R. Rzhanitsyn's theorem of duality between force and deformation parameters, the forward and backward transfer for determining the coefficients of the stiffness matrix of reinforced concrete rod structures with inclined and normal cracks have been constructed. Stiffness of structures in the zone of inclined cracks is determined using the model of composite strips which separate the zone with inclined cracks. The hypothesis about the character of deformation distribution in a complex-stressed reinforced concrete element with inclined cracks is accepted.For this model the conditional shear modulus is obtained, which allows to determine the average relative linear and angular strains of concrete and reinforcement at the point adjacent to the shear joint between inclined cracks. Based on this model and using the experimentally obtained value of the relative shear in the inclined crack, the dowel forces in the reinforcing bar intersected by the inclined crack were determined. The application of the obtained analytical relationships in the practice of designing reinforced concrete structures allows not only to clarify significantly the definition of displacements and width of opening of inclined and normal cracks, but also to maximize the convergence of the design and physical model based on experimental data.