The Special Issue ‘Insect physical control: electric field-based pest management approach’ was launched to showcase valuable new research on pest control using applied electrostatic engineering. Some phenomena generated in static and dynamic electric fields can be used to build new devices to capture or kill target insects using an attractive force or a force striking insects entering an electric field. This research field is new, and there are few researchers currently working within it. Consequently, this editorial introduces the history and general principles of electric field generation. I then discuss future directions for this field. A conductor can be electrified by connecting it to a grounded negative- or positive-voltage generator. A voltage generator is used to increase the initial voltage to achieve the desired voltage using a transformer (coil) and a Cockcroft circuit integrated into an electric circuit in the voltage generator. The difference between negative- and positive-voltage generators is that the Cockcroft circuit is set so that negative electricity  moves in the reverse direction. A negative-voltage generator draws free electrons from the ground  and supplies electrons to the conducting wire. A negative charge accumulates on the surface of the conductor. With an insulated conductor, negative charges on the conductor induce dielectric polarisation of the insulated coating of the conductor, negatively electrifying the outer surface of the insulator. A positive-voltage generator pushes free electrons to ground (an infinite sink of electrons) to positively charge the conductor (positive electrification). The surface of the conductor becomes positively charged due to electrostatic induction. In an insulated conductor, positive electrification of the conductor causes the insulating coating to become positively charged as a result of dielectric polarisation.A dynamic electric field causes the discharge of charged conductors. Factors related to the discharge of substances include the (1) voltage applied, (2) distance between poles, (3) potential difference between the two poles, (4) capacitance of the recipient receiving electricity, (5) air conductivity, and (6) volume resistivity of the insulator used for coverage. Of these factors, if an earthed conductor is one of the poles, discharge occurs more readily, as the earth receives electricity without any restriction. Assuming air is the medium, the volume of the conductive substances involved affects the insulation resistance of the air . A major factor is the vapour concentration in the air . The conductivity of the air increases with the vapour concentration, and an electric current is generated more easily in air under these conditions. Discharge is defined as electric current generation between opposite poles as a result of the dielectric breakdown of gases in the electric field by the potential difference between the poles. In a positively charged conductor, a corona discharge can change from a glow discharge (corona discharge surrounding the tip) to a streamer discharge via a brush-like discharge by increasing the applied voltage or decreasing the distance between the poles. The discharge finally breaks down into an arc discharge between the two poles. If the conductor is negatively charged, the corona is induced at lower voltages than at a positive needle pole. Although a glow corona with a short streamer discharge is generated, it does not grow and is followed by a complete breakdown in the form of an arc discharge. The strong force of a high-voltage-mediated arc discharge can dismember pests that enter an electric field.The electric field screen, first introduced in 2006, is an air-shielding apparatus based on the principles and techniques of applied electrostatic engineering . InitialThe two types of electric field screen used for insect capture were first reported in 2008  and 2011Dynamic electric fields also have potential for novel physical measures to control insect pests. Two works ,26 have Escherichia coli O-157, over postharvest crops within facilities in the food supply chain. This requires replacing the heavy metal wires passed through an insulator tube with light materials to reduce the weight of the screen. Coating the inner surface of the insulator tube with a conductive paste is a potential alternative. The use of water in an insulative tube for the screen is another possible alternative, given its high conductivity. Interestingly, various water-soluble colourings can render the screen luminous, which may be useful for analysing insect photo-selectivity. A combination of insulated and uninsulated conductive fibres could be woven into the plastic sheet of an electric field screen. These are only several possible electric field-based pest control measures. Hopefully, this editorial leads to valuable research in this new field.Future research may cover many topics. One is the installation of electric field screens on unmanned aerial vehicles for remote-controlled insect monitoring, especially flies transmitting human pathogens, like


Climbing robots are characterized by a secure surface coupling that is designed to prevent falling. The robot coupling ability is assured by an adhesion method leading to nonlinear dynamic models with time-varying parameters that affect the robot’s mobility. Additionally, the wheel friction and the force of gravity force are also relevant issues that can compromise the climbing ability if they are not well modeled. This work presents a model-based torque controller for velocity tracking in a four-wheeled climbing robot specially designed to inspect storage tanks. The model-based controller (MPC) compensates for the effects of nonlinearities due to the forces of gravity, friction, and adhesion through the dynamic and kinematic modeling of the climbing robot. Dynamic modeling is based on the Lagrange-Euler approach, which allows a better understanding of how forces and torques affect the robot’s movement. Besides, an analysis of the interaction force between the robot and the contact surface is proposed, since this force affects the motion of the climbing robot according to spatial orientation. Finally, simulations are carried out to examine the robot’s dynamics during the climbing movement, and the MPC is validated through the redrobot simulator V-REP and practical experiments. The presented results highlight the compensation of the nonlinear effects due to the robot’s climbing motion by the proposed MPC controller. Advances in technology have increased mobile robots’ versatility and expanded their application in several areas, such as maintenance and service. Service robots are commonly designed to perform tasks in structured environments into which they must overcome different obstacles and travel through specific surfaces. Climbing robots are a particular class of service robots designed to carry out different tasks in non-horizontal surfaces, such as inspection of metal structures  or assisIn the literature, a significant part of motion control strategies for mobile robotics are based on kinematic models ,4,5 thatThe adhesion force pushes the climbing robot against the surface and emphasizes the friction effect, affecting the robot’s maneuverability. The gravitational force is also a very relevant concern that cannot be neglected because it intensifies or decreases the adhesion effects due to body orientation. These aspects are commonly overlooked in 2D ground navigation since they are time-invariant. However, adhesion effects are time-varying especially, during climbing trajectories (3D navigation) through surfaces with different inclination angles.This work develops a model-based torque controller for tracking the speed of a climbing robot. The main goal of this climbing robot is to convey a NDT (Nondestructive testing) equipment such as an ultrasound phased array during an inspection task of industrial vessels. The success of the inspection task is strongly dependent on maintaining a steady speed profile during inspection. For this, the proposed torque controller takes into account the robot’s 3D position to compensate for the effects of dynamic forces during a climbing path. In the proposed model-based torque control approach, a kinematic analysis of wheel climbing robots is firstly carried out, since an inverse kinematics model will be introduced into the dynamic model supporting the control strategy. Then, a study of the dynamics discusses the robot’s behavior to derive a reliable dynamic model for the proposed model-based controller (MPC). This study is crucial to control strategy success since it is necessary to model the effects of gravity, friction force and adhesion on the movement of the climbing robot. Dynamic modeling is based on the Lagrange-Euler method that allows a better understanding of how forces and torques affect the robot’s movement. Also, a new concept of interaction strength in dynamic modeling is discussed. The frictional force is influenced by gravity and adhesion forces according to the robot’s spatial orientation. That is, an interaction force between the contact surface and the climbing robot affects the movement according to the robot’s 3D position. Therefore, the understanding of such interaction force is an essential requirement for the dynamic modeling of the climbing robot’s motion.Several works discuss the dynamic modeling of mobile robots. Meanwhile only a few articles encompasses the effects of gravity, adhesion, and friction forces into the dynamic analysis of climbing robots. Dynamic modeling of a four-wheel differential robot for trajectory tracking is presented in Caracciolo et al. . The proThe development of a reliable dynamic model for a robot allows the use of model-based predictive control (MPC - Model Predictive Control) techniques to compensate nonlinearities and to minimize the robot trajectory tracking error . For groSince the works related to climbing robots do not consider the dynamic effects of gravity, friction, and the adhesion system during robot climbing, this work contributes to bridge this gap by developing a new MPC approach to torque control of a four-wheeled climbing robot. The developed model-based torque controller considers the dynamic effects of the cited forces in the dynamic model used for speed tracking error minimization. Although the control approach is designed for a differential climbing robot, the proposed approach can be applied in other climbing robot architecture.Climbing robots are specially designed for climbing surfaces and navigating in non-parallel ground planes. Thus, they suffer different influences of gravitational force according to their relative position. The robot dynamically interacts with the surface, aiming to nullify the gravitational effects and move in any direction without losing contact with the surface. The dynamic interaction between robot and surface is specified as adhesion, which consists of an attractive force between the parts in contact, i.e., robot locomotion system and surface.Weight: the robot’s mass directly affects its ability to climb since gravity disturbs the robot’s motion. Thus, the robot must be light. Furthermore, a lightweight robot allows a better efficiency of energy, which improves its navigational autonomy;Maneuverability: the robot’s ability to easily change its direction and position is directly affected by its locomotion and adhesion mechanisms;Adhesion: the adhesion mechanisms must guarantee the adherence in different surfaces, ensuring that the climbing robot does not fall during its navigation.This kind of mobile robot is characterized by its adhesion and locomotion mechanisms , which av indicates the robot’s direction of navigation.The adhesion force should always keep the robot in contact with the surface and prevent its slippage or fall. This effect is traditionally achieved by the use of magnetic or electrostatic wheels. However, other forces can affect robot motion while climbing, such as gravity force and friction force. The interaction between the robot and contact surface during climbing can be understood from the balance analysis of several forces, which act in the coupling, as detailed and discussed in At Climbing robots are a crucial tool for the automation of inspection processes in the petrochemical industry’s storage tanks. The robot should move around the whole surface while carrying the inspection equipment and not falling when traversing dirty surfaces or when overcoming weld beads. In this situation, the controller cannot neglect the adhesion influences without the risk of falling. An example of a climbing robot for inspection tasks is discussed in . This roIn general, the papers about climbing robots using dynamic models are usually developed for ground robots. Such models do not consider the interaction between robot and environment, despising some significant effects (as adhesion and gravity) that are crucial to climbing robot modeling. Mobile robots can have their dynamic models expressed by different approaches, but the most common are Lagrange-Euler ,30,31 anIn all above cited works, regardless of the adopted approach (Newton-Euler or Lagrange-Euler), the dynamic analysis is simplified, and crucial features are ignored since the climbing robots are analyzed as a ground robot. However, as discussed, the climbing motion has some fundamental requirements that cannot be neglected during dynamic modeling. An incorrect analysis can weaken the interaction between robot and surface, causing robots to fall and damaging its structure. Thus, the present work aims to contribute to the study of climbing robots, presenting a detailed dynamic model of a wheeled climbing robot considering the friction, gravitational, and adhesion forces. The proposed model considers the interaction between the climbing robot and contact plane, including the main dynamic effects of climb tasks based on the Lagrange-Euler approach. The dynamic and kinematic analysis is developed for a differential four-wheeled climbing robot since this is the most popular topology for this kind of robot.This section brings a 2D kinematic analysis of four-wheeled climbing robots. Kinematic analysis allows us to determine the relative motion of robot wheels to generate a desired global movement. This analysis expresses the robot’s behavior in terms of velocities without any concern about dynamic effects, computing the robot motion in 2D only from its wheel’s analysis. The velocity behavior is very similar for ground and climbing robots. In both cases, the robots do not have Degrees of Freedom (DoF) to perform motion in vertical planes. A climbing robot executes non-ground movements due to its interaction (adhesion system) with a contact plane that lets it track the surface.Climbing robots are specially designed to achieve optimal adhesion during navigation over the contact plane. Thus, their topology is traditionally more complex compared to ground robots because they have unique features to guarantee a correct interaction with the surface. In this kind of mobile robot, the center of mass does not need to be in the same locus as the geometric center. Another particular characteristic is the alignment of the wheels. In climbing robot design, all wheels can be misaligned to prevent more than one wheel over-passing an obstacle at the same time, hampering a robot fall. Climbing robots’ specific characteristics introduce new requirements in conventional kinematic analysis: wheel misalignment and position of the center of mass, as shown in The locomotion systems of a climbing robot can perform three-dimensional movements through the interaction between its adhesion systems and the contact plane. Its ability to dynamically interact with the contact plane allows the surface to be tracked, even on non-ground planes. The kinematics of the climbing robot is not influenced by the robot’s spatial movement, but it is highly dependent on the robot’s topological features.G is the inertial (absolute) reference, and it is fixed on the environment  on the x-axis.The main topological feature affecting kinematic analysis is the misalignment of the wheels. Thus, inverse kinematics of climbing robots is expressed in terms of robot velocities asv/The forward kinematics can be obtained adding –8) and  and 8) ax, y and i and robot’s center of mass C. The distance vectors to each wheel are defined asf is the distance between the center of mass (C) and the robot’s center (P) on the y-axis, and e is the distance between the center of mass and the robot’s center on the x-axis.Wheel speeds should be defined concerning the global coordinate system (or absolute), but in this case, new requirements must be considered. The speed of each wheel can be expressed asThe wheel speeds can be similarly written applying the Equation  and usiny-axis is null  and purFrom Equation , the kinThe above kinematic analysis of a non-ground robot allows us to define the robot’s speed from the wheels. Also, the reference of the robot’s velocity can be changed according to its specifications. This section presented the kinematic model (Equations  to 19)))19)), anSolid knowledge about the robot’s dynamic characteristics is a fundamental requirement to successfully implement control tasks, e.g., path following and trajectory tracking. Dynamic analysis aims to describe the physical behavior of the robot considering internal  and external  aspects. This analysis expresses the robot as a set of rigid bodies that applies forces and torques in another system elements, differing from kinematic analysis that considers only geometric aspects.Climbing robots can execute motions in planes orthogonal to the ground due to their interaction (adhesion system) with the environment, as shown in Lagrange models are easy to derive and result in scalar equations, circumventing the knowledge about constraint forces and also avoiding acceleration computation needed to Newton-Euler formulation. Thus, this approach is adopted in this paper to derive the dynamic model of a climbing robot.M is the symmetric inertial matrix, V is the centripetal and Coriolis matrix, E is the interaction matrix between surface and robot including friction effects, G is the gravitational vector, B is the input matrix, A is the matrix associated with kinematic constraints, q is the generalized coordinates defined as q = The classical dynamic equation for mobile robots can be expressed, according to , as(20)Q is the generalized force vector, A is the matrix associated with kinematic constraints, and As discussed, the robot dynamic modeling based on the Lagrange-Euler approach is carried out by analyzing the kinetic and potential energy of the system. The Lagrange-Euler equation is expressed asIn climbing robots, the potential energy (U) can be disregarded in Equation  due to tThe total kinetic energy can be written asIntroducing the total kinetic energy Equation  into theThe solution of Lagrange multipliers in Equation  is not aThus, the time derivative of Equation  results Therefore, Equations –28) can can28) cAs Equation  is simplAs a result, new matrices of the dynamic model can be defined asComparing Equations  and 30)30) and uThe contribution of gravity and interaction forces must be included in the dynamic model of the climbing robot. In the next sections, the detailed analysis of these influences will be presented.x-axis), pitch (angle on the y-axis) and yaw (angle on the z-axis), resulting inm is the total mass of the climbing robot, g is the value of gravity acceleration vector x-axis anThe resistive moment E, which describes the relation of climbing robot and contact surface, can be defined asThe interaction force matrix Equation , resultiThese above presented kinematic and dynamic models of a climbing robot are used in this paper to develop a new MPC strategy for velocity tracking based on torque control in robotics.One of the most used multi-variable control techniques is the model predictive control, in which the main objective is to minimize/maximize an objective function related to a performance criterion. In general, a good performance of a MPC strategy is related to how close the model is to the system to be controlled. On the other hand, the velocity error minimization during the robot’s navigation is a well known strategy for trajectory tracking problems in robotics. Thus, a model-based controller (MPC) will be used in this paper to perform torque control for a climbing robot’s velocity tracking. The use of MPC control allows minimizing the effects of the nonlinearities present in the climbing robot.The proposed MPC controller diagram is shown in The MPC approach is based on a state-space model to design control law. Therefore the dynamic model developed in The acceleration and velocity are provided as inputs to the dynamic model. Still, since the climbing robot’s purpose is to perform the inspection, only the speed is considered a reference. During the inspection, the robot must navigate at a constant speed. Therefore, the acceleration and deceleration control is disregarded. It will be implicit in the modeling. The state variables are defined such that Simplifying the Equation (42):From the Equation , which dThe control optimization problem is defined asThe mathematical formulation of the MPC controller is given by :(48)J=∑jIn this section, the proposed model-based control approach is applied to the trajectory tracking problem of a climbing robot through simulations. First, both developed kinematic and dynamic models are validated by climbing robot performance in three different situations. Since the models are valid, the MPC controller is also essayed and validated using the simulator V-REP.An analysis of the torque behavior is carried out using three different simulated scenarios. These simulations allow to verify the dynamic and kinematic models’ performance during climbing over three surfaces with different inclination angles. In the first scenario, the robot navigates on a flat surface (0 degrees) from the point The robot trajectory planning is based on the algorithm proposed in . The plaFrom dynamic analysis in The results are shown in As expected, the robot needs a lower torque when on the flat surface than when climbing during its motion in the first scenario, since when on a flat surface, the effects of gravity and interaction force are smaller. In particular, for the third scenario, the robot required torque is growing because, at the beginning of the climb (3rd scenario), the interaction force is higher due to the sum of the reactive force to the weight and adhesion forces of the wheel. For the second situation, where the robot is already at 90 degrees, the normal force is composed only by the adhesion force, which decreases the interaction force. Thus the required torque is higher, but its profile is similar to the torque from the first scenario.The experiments to validate the MPC controller are simulated inside a virtual LPG storage spherical pressure vessel developed in the virtual experimentation platform V-REP, as shown in The parameters and limits used to tune the MPC controller are shown in The obtained results are given in A classical PI controller is also designed allowing a performance comparison with the proposed controller. The PI controller’s performance for the speed tracking of the inspection robot is shown in The next experiment aims to highlight the robustness of the proposed controller during the climb, as well as in ,38,39. TFinally, a loss of adhesion test is carried out to assess the performance of the proposed controller. The loss of adhesion occurs during a short time (around 5 s) and represents 30% of the robot’s total adhesion. It can be caused by dirt on the metallic surface. The obtained performance of the MPC controller can be seen in The purpose of this section is to study the effect of varying surface elevation angle (0 to 180 degrees) on the MPC controller performance. Therefore, to validate the MPC controller in all situations that the robot may have, various experiments were carried out by varying the robot’s climbing angle on a flat metal plate with This table gives us the average error and its standard deviation for both velocities at seven different elevations. In all situations, the MPC controller obtains an excellent performance in which medium error and standard deviation are insignificant. These good results confirm that the controller compensates the effects of gravity, adhesion, friction force, and other dynamic effects  that are correctly taken into account in the dynamic and kinematic modeling.A behavioral analysis of linear velocities is gathered in the box plot from On the other hand, there is a minor variation in the robot’s angular speed, as illustrated in The MPC controller is embedded in the real climbing robot shown in The proposed controller presents a reliable performance in the experimental results with similar behavior to evaluations in the virtual environment. The This work has discussed the kinematic and dynamic analysis of differential climbing robots. The navigation of a climbing robot presents disturbances in its dynamic parameters, due to gravity, adhesion and friction forces, which cannot be disregarded in the design of motion controllers. The Lagrange method was used to develop a complete model to a climbing robot encompassing all dynamic effects due to cited forces. The main goal was to get a more reliable model allowing a better control design to predict and compensate the disturbances caused by adhesion with the surface.In the developed dynamic model, the effects of the forces of gravity, adhesion and friction were analyzed. The gravity force was modeled according to the robot’s spatial orientation because it can vary during its navigation. Meanwhile, the interaction force concept was introduced that represents the interaction between the contact surface and the robot’s wheels about friction, adhesion, and gravity.A state-space model with integrator action was derived from the developed dynamic model that allowed the design of a Model Predictive Controller (MPC) to velocity tracking problem. Therefore, the controller can minimize the effects of unmodulated dynamic disturbances. This compensation for unmodeled disturbances is significant, since one of the applications of the climbing robot is to inspect storage tanks. During an inspection, the robot must have an accurate speed control with the smallest possible error ensuring that it navigates along the planned trajectory and correctly inspect the entire surface of the tank.The presented results, as expected, have showed that a climbing robot does not need a very high torque to move on the ground. However, even higher torque is required during the climbing movement because the robot must compensate for the effects of inertia, friction, adhesion, and gravity.The simulated results have highlighted the effectiveness of the proposed approach. For all essayed inclinations, the developed MPC controller has compensated for the dynamic effects existing during robot’s climb path. The practical results reaffirm the performance of the MPC controller in a real robot. The experiments show that dynamic modeling considering gravity, friction, and adhesion in the climbing robot was crucial to compensate for these dynamic effects.The proposed MPC controller has performed well. However, we intend, as future work, to develop a model that considers static and dynamic friction, which allows us to minimize other error in the robot’s speed. This error may be related to the uncertainties in the identified model parameters, the material surface characteristics, and the non-measurable disturbances present in the real system.


Severe acute respiratory syndrome has spread quickly throughout the world and was declared a pandemic by the World Health Organization (WHO). The pathogenic agent is a new coronavirus (SARS-CoV-2) that infects pulmonary cells with great effectiveness. In this study we focus on the codon composition for the viral protein synthesis and its relationship with the protein synthesis of the host. Our analysis reveals that SARS-CoV-2 preferred codons have poor representation of G or C nucleotides in the third position, a characteristic which could result in an unbalance in the tRNAs pools of the infected cells with serious implications in host protein synthesis. By integrating this observation with proteomic data from infected cells, we observe a reduced translation rate of host proteins associated with highly expressed genes and that they share the codon usage bias of the virus. The functional analysis of these genes suggests that this mechanism of epistasis can contribute to understanding how this virus evades the immune response and the etiology of some deleterious collateral effect as a result of the viral replication. In this manner, our finding contributes to the understanding of the SARS-CoV-2 pathogeny and could be useful for the design of a vaccine based on the live attenuated strategy. The new SARS-CoV-2 coronavirus is the causative agent of the current pandemic of COVID-19. This highly pathogenic virus has quickly become the latest threat to modern life. From the end of 2019 and up to the redaction of this paper, this virus has infected over 17 million people, leading to mild symptoms of fever and to lung function reduction, severe acute respiratory syndrome (SARS), and even death. The current global death toll stands at 670,000; however, we are still far away from determining the final mortality figure. In the absence of vaccines or effective antiviral treatments against SARS-CoV-2, it is important to understand how this virus appropriates the host translation apparatus and subverts the immune defenses of infected cells. This can be the first step in the development of novel therapeutics.As intracellular parasites, virus replication depends on the translational machinery of their cellular hosts to translate viral transcripts. Thus, virus replication requires ribosomes, tRNA, and translation factors from the cell host. On the other hand, codon usage bias is a feature of natural selection and affects the genomes of all domains of life. It is known that more frequently used codons are used for coding highly abundant proteins  and that there exist a preferential use of A-ended or U-ended codons in these genomes . Proteomic and translatomic data from infected CACO-2 cells were retrieved from Supplementary Material of Bojkova et al. . Highly expressed genes in the lung and arterial tissues were retrieved from the GTEx portal  and fO(c) are vector of 64 elements. To compute the CCorr of a given sequence s with viral ORFome, we consider the Pearson's correlation coefficient between the vector fs(c) and fO(c):Given the coding sequence We study the codon composition of two complete coronavirus genomes by measuring the percentage of G and C nucleotides at the wobble position of the codons (GC3 content). p-value = 0.024 < 0.05).As was highlighted previously, this high expression of viral proteins could lead to an imbalance in the tRNA pool needed for the normal synthesis of the proteins of the host cell. Of course, as tRNA pools depend on the cell types, the postulated imbalance could be a tissue-dependent feature. To check this hypothesis, we make use of the recently available data about the proteome profile and translational rate in SARS-CoV-2-infected cells , as it can be seen in We search for those genes, highly expressed in the lung tissue, which could be affected by the depletion of the tRNAs consumed by virus replication. They are those whose codon composition is similar to SARS-CoV-2 (CCorr > 0.25); these are listed in Furthermore, we performed a GO term enrichment analysis over the 27 genes listed in Our list of genes from lung is enriched with several ribosomal proteins that constitute both 40S  and 60S  ribosomal subunits. Many of them also appear in the set of genes derived from arterial tissue. All of them belong to the nonsense-mediated decay pathway that control the mRNAs with abnormal termination. The termination codon can be recognized if the 3′ untranslated region is short or if it does not have an exon junction complex downstream of the termination codon  belonging to the pathway of endothelial cell calcification regulated by NOTCH1 , also known as Hevin, commonly associated with regulation of cell migration and modulation of extracellular matrix proteins (Girard and Springer, The viral infection of human cells triggers an ensemble of host processes based on the interferons that interfere with viral replication. These processes have co-evolved with the viral response to the host defense, and the virus counteracts these processes through a diversity of immuno-modulatory mechanisms. For example, NS1 protein plays a central role in the influenza infection by suppressing the host IFNs response. Recent results suggest that NS1 protein can hamper the host gene expression at the translational level by obstructing the mRNA entrance tunnel of ribosomes (Thoms et al., MGP is also expressed at high levels in heart, kidney, and lung which is particularly interesting in the context of several comorbidities and collateral effects observed in the COVID-19 patients (Nikolich-Zugich et al., Summing up, if the depletion of a selected set of tRNA, induced by virus replication, affects the expression level or the co-translation folding of these proteins, one could expect the emergence of several systemic disorders.Codon usage bias is thought to have significant effects on translation rate, where rare codons are assumed to be translated more slowly than common codons (Piovesan et al., One of the main obstacles in the recent development of vaccines has been the finding of increased infectivity observed to occur after immunizations with whole virus vaccines or complete spike protein vaccines. This phenomenon has been observed both in vaccines against SARS coronavirus and in respiratory syncytial virus. However, just as the virus regulates the translation of the host by its codon usage, the biotechnological manipulation of the frequency of codons could be used to design attenuated viruses. In this sense, other vaccine strategy has been recently assayed, focusing on altering the codon-pair usage without affecting protein sequence. This codon deoptimization strategy has reduced virus replication (Coleman et al., http://corona.papers.biochem2.com; http://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD017710.Publicly available datasets were analyzed in this study. This data can be found here: LD designed the experiments. AA prepared the data. LD and AA the analyzed the data and wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Fabric-reinforced cementitious matrices (FRCM) are promising technologies that respond to today’s architectural approaches. However, due to their high strength and ductility, they are starting to be implemented in buildings as strengthening systems. In this experimental study, the amount of fiber along the load direction in high-strength cementitious matrices and the effects of the fiber orientation on FRCM mechanical properties were studied. A total of four different composites were produced with two fabrics and two matrices. Tensile and flexural tests were carried out on composites. Within the scope of microstructure studies, scanning electron microscope micrographs were obtained and analyzed, along with microtopography sections. The main result obtained from the study indicates that as the fiber area in the direction of the load increases, the load order carried in this direction increases. However, this increase does not have to be proportional to the fiber area used in the direction of the load. The fiber coating and coating matrix interface play important roles in a composite’s performance. The carbon fibers can be used more efficiently by using them along the load direction and the loads in the matrix can be transferred to the carbon fibers by creating a larger fiber–matrix interface area. Cementitious materials with high compressive strength, low tensile strength, and high toughness are generally strengthened with reinforcement. In existing applications, conventional concrete reinforcement steels are used as reinforcement. Reinforced concrete is a system that has been widely used all over the world for decades. Reinforced concrete has proved itself by showing success under many conditions. Accordingly, the calculation methods have improved considerably and engineers have a high level of experience and confidence in reinforced concrete calculation methods. However, reinforced concrete elements should be designed with certain dimensions to provide the desired performance ,2,3. In Composites produced using the mentioned fabrics are called fabric-reinforced cementitious matrices (FRCMs) or textile-reinforced mortars (TRM). FRCM composites can be obtained using different fabrics and different matrices. The raw materials of fabrics are similar to those of fibers and can be glass, basalt, carbon, polypropylene, polyvinyl alcohol, sisal, and p-phenylene benzobis oxazole ,15,16,17Composites obtained using low-, normal-, and high-strength matrices are used in many fields. These composites are used in the production of some structural elements , permaneIn addition to high-strength concretes, ultra-high-performance matrices are also used in FRCM production in practice. In ultra-high-performance concretes, discrete fibers are often used to obtain high ductility and toughness levels in concretes . The bonCementitious matrices with fabric reinforcement are generally characterized by tensile and flexural test results. Although flexural tests are sufficient for composites used for exterior cladding, it is recommended to do tensile tests on composites used as strengthening systems. Tensile experiments are usually carried out according to two regulations. One of these documents is International Union of Laboratories and Experts in Construction Materials, Systems and Structures Technical Committee 232 Recommendation (RILEM 232) , while tIn this experimental study, the carbon fabric produced by using carbon fibers in different proportions in two different directions was used in high-strength matrices. Fabric-reinforced cementitious matrix (FRCM) composites were produced by employing these fabrics in two different types of high-strength cementitious matrices. The properties of the produced FRCM composites were investigated. Tensile and flexural tests were performed on composites produced with two different matrices and two different carbon fabrics. In addition, microstructural investigations were performed with a scanning electron microscope (SEM).Energy is used in the production of carbon fibers. Using these fibers with a smart design to avoid overuse in composites will help protect the environment, as well as prevent high costs. Cladding panels, one of the two main uses of FRCMs, are generally supported along their length. Higher tensile stresses occur in the length direction. To carry high tensile stresses, a high amount of reinforcement is also required. When stresses are successfully carried along the long span direction, there will be no need for reinforcement in the short span direction. The second use area of FRCM composites is strengthening against earthquake loads. The reinforcements in the direction corresponding to the tensile stress work actively, while in the other direction the reinforcements are subordinate. In the directions where the composite is not subjected to any load or subjected to very low loads, instead of using carbon fibers, the use of e-glass fibers will prevent unnecessary use of carbon fibers. In this way, the aim is to achieve a similar performance by using less carbon fiber or to obtain superior performance by using the same amount of carbon fiber. The performances of composites with high-volume carbon fiber along the beneficial direction: (CL fabrics), carbon along the primary direction and e-glass along the secondary direction, and the composites produced with only carbon: (C fabrics), equal amounts of carbon fiber in both directions, in high-strength matrices were experimentally compared. Ensuring that carbon fibers carry a load close to their capacity is also important for the efficient use of resources. When using commercial carbon fabrics without designing the composite, the loads on the carbon fibers are far below the fiber load-carrying capacity. In previous studies, this has not been emphasized enough. Here, it is necessary to increase the stresses on carbon fibers to use carbon fibers more efficiently. For this reason, it is thought that the use of fabrics produced with yarns containing less fiber and more surface coating could be effective. In this study, in the composites with two different carbon amounts in the same direction in two high-strength cementitious matrices, the stresses on the carbon fibers and on the entire composite section are addressed. In this context, the novelty of the study is, addressing the more efficient use of carbon fabrics in high-strength matrices by employing the carbon fibers in the beneficial direction and changing the amount of coating per unit fiber area.In the experimental study, two different ready dry mix high-strength mortars and two different carbon fabrics were used. The ready mixes used have characteristic strengths of 60 MPa  and 120 MPa . M60 mortar is a thixotropic mortar that can be applied on vertical surfaces, however M120 mortar is a self-leveling mortar. CEM1 52.5 cement , dry-state polycarboxylate-based superplasticizer, quartz-based aggregate, and mineral additives were used when both of the mortars were produced. The maximum particle size of the quartz-based aggregate used is 1 mm. While F class fly ash is used as a mineral additive in the production of M60 mortar, silica fume is used as the mineral additive in the production of M120 mortar. Mortars are mixed in the laboratory using the amount of water specified by the manufacturer. The mixing speed was 600 rpm. The prepared mortars were cast into 40 mm × 40 mm × 160 mm molds and compressive strengths were obtained after 28 days.2/m were designed and produced in the warp and weft directions. It contains equal amounts of carbon fiber in both directions. These fabrics will be abbreviated as (C) in the next part of the paper. For the second type of carbon fabric, all of carbon fibers were assigned in the warp direction. In the weft direction, e-glass glass fibers were used for the assembly of carbon fibers. The amount of carbon fiber in the warp direction in this fabric was 105 mm2/m. These fabrics will be abbreviated as (CL) in the next part of the paper. Initially, CL fabric was aimed to use twice as much fiber as C fabric in the warp direction. However, due to the fact that the production technique used on production lines does not allow the use of this ratio, using exactly twice the amount of carbon fiber as the C fabric in the warp direction was not possible. The amount was considered to be 20% more than twice the amount of carbon fiber as the C fabric in the warp direction. Both fabrics are coated with styrene butadiene rubber (SBR) for ease of handling and application. Both fabrics used in the production of the composites are shown in When designing carbon fabrics, the aim is to reveal the effects of the carbon fibers on the beneficial properties of FRCM composites. The tensile strength of the carbon fiber was 3600 MPa according to the producer’s declaration. Two different carbon fabrics were designed for targeted analysis. For the first of these, fabrics with a carbon fiber area of 44 mmPlywood molds were prepared according to sample sizes for the production of composite samples. The sample sizes were chosen as 600 mm × 130 mm × 20 mm for tensile test samples and 300 mm × 100 mm × 20 mm for flexural test samples. Since the M120 matrix is self-leveling, the reinforcements were fixed by stapling the mold edges. Then, the self-leveling M120 mortar was poured into the mold and the production of the composite was completed. The production stages of composites produced with M120 matrix are shown in While creating sample codes, the matrix and carbon fabric codes were used. The first notation in the sample code indicates the matrix, while the second notation represents the carbon fabric type. For example, M120CL refers to the composite produced with a mortar, with a characteristic strength of 120 MPa and containing the fabric in which carbon (CL) is used in one direction.Five samples were produced for each series of experiments. The composites produced were removed from the molds on the day after production and isolated from the external environment using polyethylene stretch film for 26 days until the day of the experiment. The samples prepared for the tensile and flexural tests were then stored in the laboratory until the day of the experiment. For the tensile test, the steel apparatus was glued to the samples as described in the ICC-ES C434 document . The appThe MTS Criterion C43 504E  universal deformation-controlled servo test system was used for flexural and tensile tests. The capacity of the test system is 50 kN. The laboratory temperature was measured as 18 ± 2 °C during the tests. Flexural tests were carried out as a four-point bending test. In the flexural tests, the support span length was chosen as 300 mm. During the flexural tests, the strain rate was chosen as 0.6 mm./s. After the metal plates were glued onto the samples in the tensile tests, the metal plates were attached to the steel connectors, which were movable in both directions at both ends. The purpose of applying these steel connectors is not to create any eccentricity during the tensile test. Then, the frame on which deformations were measured was placed on the sample. The length of the frame in which the extensions were measured was 120 mm. Deformations were obtained using linear variable displacement transducers (LVDT) from two points in the middle axis of the sample, at the front and back. The average of the extensions obtained from both LVDTs was taken as the extension of the sample. Tensile tests were carried out with deformation control. Elongation was controlled from the crosshead movement. During the pulling experiments, the crosshead velocity was programmed as 0.8 N/s. The test systems used in the tensile and flexure tests are given in After the samples taken from the mortars were cured in lime-saturated water at 23 ± 2 °C for 28 days, compressive strength tests were applied. As a result of the compressive strength tests, the average strengths of the samples taken from M60 and M120 mortars were obtained as 76 MPa and 132 MPa, respectively.2/m carbon fiber in the warp and weft directions. For the second type of composite produced with the M60 matrix, the M60CL composite includes fabric (CL) containing 105 mm2/m carbon fiber along the warp direction and e-glass fiber along the weft direction. The graphics obtained from the data for the tensile tests are shown in Two different types of composites were produced with the M60 matrix. The first composite was obtained by using the M60 matrix and C fabric, which uses carbon fiber in both directions. This fabric uses 44 mmAccording to In both In The examination of the flexural behavior of composites produced with the M60 matrix in The tensile test results of the FRCM composites produced with M120 mortar are presented in In For the composites produced with ultra-high-strength M120 mortar, critical points in the tensile test results are shown in In In In In the experiments on the composite, regardless of the amount of fiber in the direction of loading, the parts of the graphs until the first crack occurs depend on the matrix properties and are managed by the matrix. After the first cracks had occurred, the multiple cracking mechanism was activated in all samples in tensile and flexural tests and strain hardening behavior was observed. In tensile tests, the load suddenly dropped to zero after the maximum load was reached in all of the samples, and then failure occurred. In flexural tests, while samples produced with the CL fabric and M60 composites showed strain softening behavior, composites produced with M120 mortar showed similar strain softening behavior when using the C fabric. The strain softening behavior affects the ductility of the sample in flexural tests. If carbon fibers are used in a beneficial direction, the mechanical energy absorbed in the stage after the maximum load is reached is higher;The first crack loads were not significantly different when different fabrics were used for flexure and tensile tests. The maximum loads increased when CL fabric was used. With the increase of fiber area in the direction of the load, the load order carried along this direction increases. However, this increase does not have to be proportional to the fiber area used in the direction of the load. Improvement of the matrix properties over 60 MPa has no significant effect on composite mechanical properties;Regarding the performance of high-strength cementitious mortar and carbon fiber composites, the interface of the coatings with the carbon fiber or cementitious matrix affects the performance. The fibers, fiber–matrix interface, coating material, and matrix properties should be optimized to give best performance for the composite. Optimization can be done by modeling the peel-off strengths of the coating on the fibers. It should be noted that the defects in the interface and elements that disrupt the homogeneity significantly affect composite performance;When the residual amounts of high-strength cementitious matrix on the SBR-coated carbon fiber fabric were examined, it was clear that the SBR coating provided sufficient adherence for the cementitious matrix. In the microtopography studies, it was found that the high-strength matrix had better adhesion to the coating. However, factors such as the coating type and coating thickness should be taken into consideration regarding the composite performance;The thickness of the coating takes advantage of the performance of the fibers and transfers the loads on the coating to the fibers. The parts with low coating thickness were peeled off over the carbon fibers;By reducing the amount of carbon fiber along the load-carrying direction, the amount of coating corresponding to the unit area of the carbon fiber is increased. The carbon fibers can be used more efficiently and the loads in the matrix can be transferred to the carbon fibers through the coating–matrix interface, allowing the carbon fibers to carry more loads. Thus, carbon fibers can be used more efficiently by carrying closer loads. It has been demonstrated that the increase in the ratio of the carbon fiber to the cement matrix interface per unit area of carbon fiber is effective in increasing the load transferred to carbon fibers. Using more carbon fibers in one direction increases the load-bearing capacity of the composite in terms of tensile strength and bending. However, using a higher yarn numbers with thinner yarn will further increase the tensile stresses on the fiber and the overall load-carrying capacity;Further studies could investigate which coatings might be optimized by performing experimental studies on different coating types, as well as which carbon fiber thicknesses should be used.The more efficient usability of carbon fabrics in high-strength cementitious matrices by employing the carbon fibers in the beneficial direction and changing the amount of coating per unit fiber area was investigated experimentally. The following conclusions can be drawn according to the results obtained from the experimental study, within the limits of the materials used:


Inertial measurement unit (IMU)-based gait analysis systems have become popular in clinical environments because of their low cost and quantitative measurement capability. When a shank is selected as the IMU mounting position, an inverted pendulum model (IPM) can accurately estimate its spatial gait parameters. However, the stride-by-stride estimation of gait parameters using one IMU on each shank and the IPMs has not been validated. This study validated a spatial gait parameter estimation method using a shank-based IMU system. Spatial parameters were estimated via the double integration of the linear acceleration transformed by the IMU orientation information. To reduce the integral drift error, an IPM, applied with a linear error model, was introduced at the mid-stance to estimate the update velocity. the gait data of 16 healthy participants that walked normally and slowly were used. The results were validated by comparison with those extracted from an optical motion-capture system; the results showed strong correlation ( In particular, the inverted pendulum model (IPM) is considered useful for estimating spatial gait parameters such as stride length from acceleration and angular velocities measured by the IMU3. However, the step-by-step accuracy of the spatial parameters estimated using the IMU data and IPM model has not been validated thus far.In recent years, many studies have focused on the development of an inertial measurement unit (IMU) equipped with an accelerometer, gyroscope sensor, and magnetometer for a gait analysis system that can provide quantitative gait parameters such as stride length, velocity, gait cycle. Compared to the golden standard for gait analysis—a motion capture system and instrumented walkways—the IMU-based system is cost effective, lightweight, and versatile, which are suitable characteristics for clinical and residential applications4. For example, variability in stride length can be used to assess the progression of Parkinson’s disease (PD)5, and stride velocity can be used to predict the risk of adverse events in the elderly6. To estimate spatial gait parameters from acceleration and angular velocities measured by the IMU, the previous studies implemented a segmentation algorithm10. Integral computations for spatial parameter estimation are reset at each segmentation point, which reduces errors caused by the measurement noise. The implementation details of these algorithms depend on the attachment position of the IMU because different positions produce different signal characteristics and different assumptions need to be considered to improve estimation accuracy. A wide selection of attachment positions for the IMUs involved bilateral shanks11, bilateral insteps15, and bilateral heels17. In terms of ensuring attachment stability, the shank position seems to be a good choice because the soft tissue of the lower shank has less movement than that at the other positions18. Further, when the IMU is fixed to the heel or instep position on footwear, the moving artifact of the footwear affects the estimation accuracy. However, compared to the heel or instep attachment positions closer to the ground, the shank position has room for improvement in terms of estimating spatial parameters such as stride length and stride velocity. The shank-based method can be used to obtain reliable gait parameters and visualise the 3D-trajectory of each stride20. In a previous study, zero-velocity-update (ZUPT) was introduced, which re-initialises the integrated velocity to zero at the segmentation point (mid-stance). However, the shank possesses a small velocity at the mid-stance2, which results in the error being included in the estimated spatial gait parameters. Instead of assuming the velocity at the mid-stance to be zero, the inverted pendulum model (IPM)3, which considers the IMU movement at the mid-stance as a circular motion in the sagittal plane and estimates the velocity using angular velocity has the potential to provide a more accurate result. In fact, Wu et al. showed that the total error of the walking distance estimated using shank-mounted IMUs and an IPM was smaller than that estimated using the same IMUs and a ZUPT19.Kinematics information in the gait cycle is a component of gait considered in clinical gait analyses20 as the ZUPT method because this method had been evaluated for stride-by-stride spatial gait parameters.However, it remains unclear if stride-by-stride estimation using shank-mounted IMUs and the IPM is superior to that using ZUPT. As mentioned above, some variability in the spatial gait parameters is important for the gait assessment of people with gait disorders, and to investigate such variability in gait parameters, stride-by-stride estimation of gait parameters is necessary. This study aimed to validate the stride-by-stride estimation method for spatial gait parameters using shank-mounted IMUs and the IPM. In addition, we investigated whether the stride-by-stride estimation of the spatial gait parameters using the IPM was superior to that using the ZUPT. A modified IPM that considered the posture of the IMU for shank trajectory estimation was implemented. For evaluating the proposed method, we performed a concurrent validation experiment using an optical motion capture system with a high spatial resolution. Next, we compared the proposed method to a ZUPT method to investigate whether the IPM improved the accuracy of the stride-by-stride estimation. We used a previously reported methodAll 16 participants completed both tasks; the data for the normal speed task of one of the participants could not be analysed because of synchronisation issues (the motion capture system did not capture the stamp event), and therefore, it was excluded. The motion capture system suffered from loss of data because of the reflective markers; these invalid data were excluded, and a total of 695 strides were extracted from the motion capture system, with 283 strides for the normal speed task and 412 strides for the slower speed task.First, we validated the proposed method compared to the results from the motion capture system. Figure Second, we investigated whether the proposed method estimated the parameters more accurately than the previous method. The Bland–Altman plots for the parameters estimated using the proposed method and a previous method are shown in Fig. This study aimed to validate stride-by-stride gait estimation using IMUs attached to the shank and an IPM. The parameters were extracted from the walking data of 16 participants, and they were compared with those obtained using a motion capture system as reference. The results showed high correlation and good agreement between the two systems for stride length, stride velocity, and shank vertical displacement, which verifies the technical effectiveness of the proposed method.21. The relative absolute error of the shank vertical displacement is slightly worse than other parameters with an overall value of 6.5%  were mounted on the shanks on both sides, immediately above the malleolus at a distance of 7  and toe-off (TO) events were first detected based on the angular velocity in the sagittal plane ωz7 Fig. . The seaS and E represent the IMU coordinate frame and the laboratory coordinate frame, respectively. Further, we use (k) to represent the kth sample of an instantaneous variable and (i) to represent a variable in the ith gait cycle. For example, S to frame E. In addition, ms(i) is the mid-stance event in the ith gait cycle.The quaternion system was introduced to describe orientation information in this study. We use superscripts to represent the coordinate frame wherein a variable is located and the rotation direction of a quaternion. Superscripts ms(i), we assumed that the IMU is reset and the accelerometer only detects gravity. Therefore, the rotation quaternion ms(i) is computed using the accelerometer output At each The remaining rotation quaternions in each segment were computed via the integration of angular velocity Using Finally, the linear acceleration After linear acceleration is determined, the velocity ms(i), we assume the movement of the shank to be rotational motion with the malleolus as a fulcrum  can be calculated as the cross product between the angular velocity in the laboratory coordinate frame ms(i), and therefore, r asr is known in advance and there is no need to measure it each time.However, this integral result contains significant drift. This drift occurs from the accumulation of sensor errors such as bias in the gyroscope and jitter in the accelerometer. To solve this problem, a modified IPM was introduced in this phase. At each rum Fig. . Thus, t31 that occurs over time with a constant slope and intercept in each segment asith gait cycle, respectively.Then, we model the drift error Using the velocity P is introduced for visualising the stride trajectory and computing the spatial parameters. In frame P, the y axis direction is aligned to the stride forward direction and the x axis is aligned along the vertical direction. The rotation matrix P and E is computed by solving the equationFirst, the trajectory y direction x direction The definitions of stride length and shank vertical displacement are shown in Fig. In this study, six females and ten males  with features of an accelerometer  and optical motion capture software  was used as the reference system. The motion capture system was calibrated well to ensure that the overall displacement error was under 34 was introduced to assess the agreement between the IMU and the motion-capture measurement system for the previous20 and proposed methods.For the statistical analysis, we compute the difference in the stride-by-stride gait parameter results extracted using the IMU and the motion-capture system as the error for the proposed method. We computed the mean and standard deviation of the error, the absolute error, and the relative absolute error for each parameter. Further, Bland–Altman analysis20. All strides can be found in the IMU estimation results without missing detection. Thus, we analyzed these data to validate the proposed method.One participants’ data in normal speed was excluded because the motion capture data cannot be synchronized with the IMU data. Finally, 15 normal speed data and 16 slower speed data were analyzed. After removing invalid data resulting from the reflective markers loss in the invisible area, a total of 722 strides were extracted from the motion capture system, with 289 strides (19.27 strides per one participant) in the normal speed task and 433 strides (27.06 strides per one participant) from the slower speed task. The number of strides analyzed is not less than that measured in previous studies


Vehicle wheel alignment inspection is generally carried out using a computer vision-based system. Due to its inspection mechanism using four wheel centers, the computer vision-based system cannot be applied to the wheel alignment inspection of suspension module units. However, when a vehicle suspension module is being developed, there is no complete car ready for wheel alignment inspection even though it is a very important procedure for suspension property tests. This study proposes a novel and efficient way to inspect vehicle wheel alignment for suspension modules. Two laser modules and several mechanical jigs were employed for wheel alignment inspection, allowing the toe and camber angles of the suspension module to be measured. For accurate wheel alignment results, calibration of the laser modules was performed prior to the inspection. This calibration procedure adjusts the yaw and pitch angles of the laser module so that they can be orthogonal to the mounting jig. For the calibration, a novel method of using laser straightness was adopted and, consequently, 0.02 degrees of orthogonality was achieved. The wheel alignment inspection results were determined then verified using a vision system with two cameras. In order to use this vision system, two cameras were used and a new method of modifying the measurement mechanism was developed. According to the verification results, the proposed wheel alignment inspection provided very high measurement accuracy. The wheel alignment inspection mechanism proposed in this study can not only give very reliable results but also provide a cost-efficient method of inspecting the wheel alignment of suspension modules to automakers. Vehicle wheel alignment inspection is generally conducted in automobile maintenance shops. It includes the measurement of the steering axis inclination (SAI), caster angle, camber angle, and toe angle. SAI ) and caster angle are the inward and backward tilt, respectively, of the suspension toward the center of the vehicle. They are determined by the positions of the upper and lower ball joint pivots, which are geometrically unchanged and thus not adjustable once the vehicle has been designed. Camber angle is the inward or outward tilt of the front tires as viewed from the front, and toe angle is the side-to-side difference in distance between the front and rear of the front tires. These camber and toe angles are adjustable and should be continuously managed by the vehicle owner, because if a vehicle has incorrect camber and toe angles, the vehicle can experience several issues such as uneven tire wear, steering wheel pulling, steering wheel shimmy, and sometimes serious vehicle vibration ,2.Wheel alignment inspection in automobile maintenance shops is generally conducted by a computer vison-based system ,4 compriWhen a new vehicle goes into production, its mechanical and electronic modules are manufactured and tested before they are installed in the vehicle. For instance, a suspension module, which is composed of a sub-frame, suspension springs, shock absorbers, lower and upper arms, knuckles, rubber bushes, stabilizer links, and a stabilizer bar, is produced and tested before it is installed into the vehicle. There have been several studies that can be applied to the wheel alignment inspection of suspension modules. Dongyoub Baek has proposed a simple and inexpensive method using a consumer-grade depth-sensing camera such as Kinect to replace the computer vision-based system . The metThis study proposes a new and cost-efficient method to inspect vehicle wheel alignments for suspension modules. The proposed method employs two laser modules that are mounted into the wheel knuckles. With the laser modules, toe and camber angles can be measured by measuring the distance of the laser mark projected on the opposite side of the laser mounting jig. For accurate wheel alignment results, the calibration procedure of the laser module—which makes the laser module perfectly orthogonal to the laser mounting jig—was performed before wheel alignment inspection. After the wheel alignment inspection, the results were verified by a vision system. For the verification, a new method using complementary metal-oxide semiconductor (CMOS) cameras was also developed.The wheel alignment inspection method proposed in this study can provide very accurate results and a cost-efficient way for automakers to inspect the wheel alignment of suspension modules. In addition, it can be also applied in the wheel alignment inspection of motorcycles and unconventional automobiles ,13.The typical wheel alignment inspection for a full car uses a computer vision-based system ,15. FiguA1, nA2, nA3, and nA4) are obtained, as shown in B), as shown in A and nB, 90-α is the camber angle. A total of four camber angles can be obtained from each plane of the wheels. On the other hand, when nA is projected onto Plane B, it creates a vector (nA’), and the angle between nA’ and the centerline of two front wheels is the toe angle of the front wheels. A total of four toe angles can be obtained.When all target boards are mounted on the wheels, the technician turns the steering wheel to the left and right ends to determine the neutral position of the front wheels. Then, the steering wheel is positioned at the neutral position and the technician moves the vehicle back and forth. By moving the vehicle back and forth, each plane of four wheels  and their normal vectors  3D Space CreationThere are many ways to create a 3D space using cameras ,20,21. I(ii) Absolute Coordinate CreationRetro-reflective markers were also placed on the target wheel plates. In addition to the markers, there were single-dot-type markers along the rim of the target wheel plates, as shown in (iii) Local Coordinate Creation and Wheel Alignment InspectionTwo local coordinates are created at each wheel by transferring the absolute coordinate to each wheel, and the toe and camber angles are obtained by the angular differences between the local coordinate and the target wheel plane, as shown in Verification tests were performed three times for each wheel, and the results are shown in The proposed wheel alignment inspection method uses two laser modules that are mounted into the wheel knuckles, and the toe and camber angles are determined by measuring the distance of the laser mark projected onto the opposite side of the laser mounting jig. Because of this measurement approach, when both wheels have non-null toe and camber angles, it can affect the measurement results. For instance, if the left wheel exhibits one degree of camber angle, then it basically has 36.53 mm of the laser mark distance on the right side of the knuckle plate. However, if the right wheel exhibits one degree of camber angle at the same time, then the laser mark distance of the left wheel becomes 36.534 mm, which is 1.00011 degrees. Therefore, this error can be negligible. Furthermore, the measurement results can also be affected by the manufacturing tolerances of the jigs. Especially for the knuckle jigs, the parallelism and perpendicularity tolerances may be critical to the measurement results. In this study, in order to prevent measurement errors, the parallelism and perpendicularity tolerances of the knuckle jigs were 0.01 mm and the surface roughness was 0.1 This study proposes a novel method for vehicle wheel alignment inspection. Unlike the wheel alignment inspection for full cars, which makes use of four wheel centers to measure toe and camber angles, wheel alignment inspection of a suspension module in development requires a new approach, since one suspension module has only two wheel centers. This study employed two laser modules for inspecting the wheel alignment of suspension modules in development. Two laser modules were orthogonally mounted onto the jigs of the left and right wheel knuckles, and each beam from the two laser sources was projected onto the other jig plane. By measuring the horizontal and vertical distances of the laser marks from the laser sources, the toe and camber angles of each wheel plane were obtained. The measurement accuracy of the proposed wheel alignment inspection can be guaranteed only when perfect orthogonality between the jig and the laser module is achieved. For perfect orthogonality, the angle between the jig and the laser module was precisely adjusted by rotating the laser module. Using a laser module mounted on the jig and a plane board placed at the far end of the laser module, the laser beam mark drew a circle on the board as the laser module rotates. By measuring and minimizing the diameter of the circle, the orthogonality between the jig and laser module was adjusted. By means of adjustment, 0.02 degrees of orthogonality was achieved.After setting up the wheel alignment conditions for a suspension module using several experimental parts such as a U-beam, surface table, pillars, and jigs, the wheel alignment inspection for the suspension module was performed. In this study, a vision system with two CMOS cameras was employed to verify the proposed wheel alignment inspection method. For the verification, two ultra-high resolution CMOS cameras were used and a 3D space were created by the cameras. In this 3D space, one absolute coordinate system from two wheel centers was created and two local coordinate systems at each wheel center were also created. By measuring the rotation angles between the absolute and local coordinate systems, the toe and camber angles of each wheel plane were obtained. From the verification results, it can be seen that the proposed wheel alignment inspection using laser modules can provide very accurate measurement results.The wheel alignment inspection proposed in this study can not only give very reliable results but was also very quick and cost-efficient. Therefore, it can save time and cost for automakers.