In addition, the sensitive analysis results indicated that the rubber and cement are the most important parameters for predicting the strength and energy absorption properties, respectively. Accordingly, the improved POA-RF model not only is proven as an effective method to predict the strength and energy absorption properties of aseismic materials, but also this hybrid model provides a new idea for assessing other aseismic performances in the field of tunnel engineering.The application of aseismic materials in foundation engineering structures is an inevitable trend and research hotspot of earthquake resistance, especially in tunnel engineering. In this study, the pelican optimization algorithm (POA) is improved using the Latin hypercube sampling (LHS) method and the Chaotic mapping (CM) method to optimize the random forest (RF) model for predicting the aseismic performance of a novel aseismic rubber-concrete material. Seventy uniaxial compression tests and seventy impact tests were conducted to quantify this aseismic material performance, i.e., strength and energy absorption properties and four other artificial intelligence models were generated to compare the predictive performance with the proposed hybrid RF models. The performance evaluation results showed that the LHSPOA-RF model has the best prediction performance among all the models for predicting the strength and energy absorption property of this novel aseismic concrete material in both the training and testing phases (R The research and development of aseismic concrete materials is of great significance to reducing the damage caused by earthquakes on tunnel structures. To determine the material’s performance and decide its application in the field of tunnel engineering, the strength and energy absorption properties are widely used as the main performance evaluation indices ,2,3,4. AReviewing the published research, the experiment tests are direct methods to calculate the strength and energy absorption properties of the rubber-concrete material . The strIn recent years, soft computing represented by machine learning (ML) has made remarkable achievements in the prediction of rubber-concrete material performance, e.g., artificial neural networks (ANN) ,13, suppTherefore, an optimized RF model using the pelican optimization algorithm (POA) is proposed to predict the strength and energy absorption properties of a novel aseismic rubber-concrete material in this study. Two functions named Latin hypercube sampling (LHS) and Chaotic mapping (CM) are adopted to improve the initial population of POA. In total, 140 concrete specimens are generated to test their strength (70 specimens) and energy absorption property (70 specimens) for training the prediction models. Four statistical indices are utilized to evaluate the predictive performance of the improved POA-based RF model and other comparison models. Finally, sensitive analysis is responsible for calculating the parameters’ importance in the strength and energy absorption property prediction.As a new functional material with special uses, rubber-concrete material is mainly aimed at weakening the dynamic impact of engineering structures under strong earthquake disturbance. The incorporation of rubber means more impact energy is absorbed and converted into other forms of energy removal, but also leads to the reduction of the rubber concrete’s strength. A traditional uniaxial compression test and an impact test based on the SHPB device are the main technical approaches to measure the strength and energy absorption properties of aseismic materials. Although the test results are accurate, sample preparation and equipment operation are extremely time consuming. In the face of urgent engineering needs, the performance estimation of seismic materials without timely estimation is bound to delay the construction period and bring certain economic losses. Moreover, ordinary experimental results and regression analysis cannot accurately grasp the nonlinear relationship between material properties, material proportions, geometric properties and material performance. Therefore, the development of a novel performance estimation method is of great significance for the close fit between novel seismic materials and practical engineering.Soft computing represented by ML models may be used to learn this nonlinear relationship and make fast and accurate predictions of a material’s performance. This study contributes (a) to the development of a novel aseismic concrete material consisting of rubber, sand and concrete and (b) to the accurate prediction of the strength and energy absorption properties of aseismic material, which is significant to get rid of the miscellaneous material performance tests based on large-scale equipment and to measure them in real time in field engineering. The improved POA-RF model is provided to estimate the strength and energy absorption properties of a novel aseismic rubber-concrete material using an actual database collected from a series of performance tests in this study.To enhance tunnel stability under earthquake resistance, a novel aseismic concrete material doped with rubber and river sand is developed and its performance is assessed. The rubber is responsible for increasing the elasticity and damping of the novel aseismic material, and the river sand is utilized to provide enough strength for it. Although some novel fine aggregates were put forward instead of river sand, e.g., blast furnace slag , waste gBefore testing the strength and energy absorption properties of a novel aseismic rubber-concrete material, the concrete specimens should be prepared according to the test standards, and the production procedure is shown in It should be noted that each specimen is independent and non-repetitive, such as composition content , physical properties (mass and density) and size (diameter and length). The detailed information of the considered parameters is listed in Random forest (RF) is generally regarded as an excellent integrated machine learning model for solving classification and prediction problems. The significant advantage of this model is the data utilization and performance evaluation mechanism, i.e., bootstrap resampling technology is responsible for randomly selecting most data from the original database (the ratio is two to three) to form the decision trees (DTs) and the rest of data is utilized to establish the test set for evaluating the DTs performance; the final performance of the RF model is determined by using the average value of the predicted values of all DTs.t) and the random features (Maxdepth) are the main hyperparameters that affect its prediction performance. Although the increase of the Nt will not cause the overfitting of the model, it is difficult to obtain satisfactory predictive performance through the time-consuming manual debugging of hyperparameters’ combinations [As illustrated in inations ,39.Trojovský and Dehghani  proposedi-th pelican. I indicates the maximum number of pelicans. (a) Population initialization: Pelicans generally search for prey within a certain range of search space, so the initial position of each pelican in the population is random and can be expressed as:U is also a random number (1 or 2).(b) Exploration phase: At this stage, the main goal of pelicans is to find and determine the prey position and change their positions in preparation for an attack. Therefore, the position of each pelican is updated using Equation (4):z is a random number (0 or 2). T is the maximum number of iterations, and t represents the current iteration.(c) Exploitation phase: Once the pelican is in a good position and launches an attack, i.e., flying across the water and pushing the fish up into its throat pouch. This strategy can be mathematically expressed as:For the metaheuristic optimization algorithms-based SI, the incompatibility of population initialization results in low precision and an easy to fall into local minimum problem . Numeroui-th and i+1-th chaotic sequence of the logistic mapping function, respectively. i-th pelican. The aim of the CM method is to use mapping functions to generate a more diverse population of the POA. The logistic mapping function is a popular method to achieve this goal ,54, whici-th pelican. k and K indicate the current dimension of pelican and the maximum dimension of the search space, respectively.The function of the LHS is to stratify the initial positions in three-dimensional space, and then conduct random sampling and disrupt the order of each sample to obtain a more stable and diverse population. Therefore, the new population can be described as follows:t and Maxdepth are  and , respectively; (c) Performance evaluation—four statistical indices were used to evaluate the predictive performance of the proposed hybrid RF models.Two improved optimization algorithms consisting of Latin hypercube sampling-POA (LHSPOA) and chaotic mapping-POA (CMPOA) are used to optimize the RF model for predicting the UCS and the ETR of a novel aseismic rubber-concrete material in this study. As illustrated in 2) is also known as goodness of fit, which reflects the interpretation of the predicted value to the measured value from the fitting perspective. If R2 is equal to 1, that means the prediction model is perfect. The variance accounted for (VAF) is often used to evaluate the degree to which the prediction model can explain the variance of the considered data. The function of the root mean square error (RMSE) is to evaluate the model performance by measuring the error between the predicted value and the measured value. In addition, the mean absolute error (MAE) can further reflect the real situation of error. These statistical indices have been considered to verify the performance of different prediction models for solving the regression problem [T indicates the number of used samples. tm and tp represent the t-th measured and predicted values, respectively. In this study, four indices were used to evaluate the performance of the proposed models for predicting the UCS and the ETR of the novel aseismic concrete material. The determination coefficient  for predicting the UCS, but also obtained better performance indices  than other models in the ETR prediction. After this model, the performance indices of the CMPOA-RF model are also better than the POA-RF for predicting the UCS and ETR.After establishing the optimal hybrid RF models, each model was first utilized to predict the UCS and the ETR of this novel aseismic concrete material based on the train set. The performance indices of all the models are listed in 2 and RMSE in the same set are 4 and 1, respectively. As demonstrated in In addition, the rank score is a useful tool to evaluate the model performance by calculating the score of all the performance indices. For example, the score values corresponding to the highest values of R2 (0.9857 and 0.9065) and VAF (98.5909% and 91.3652%), and the lowest values of RMSE (0.5781 and 1.8814) and MAE (0.4233 and 0.9913). After the LHSPOA-RF model, the CMPOA-RF model has better performance indices than the POA-RF model for predicting the UCS and the ETR.However, the performance evaluation of the model in the training phase is not enough to prove its real prediction performance, especially as it is applied to predict unknown data. Therefore, the test set is responsible for verifying the performance of the proposed models for predicting the UCS and the ETR. The ranking score results of the proposed models for predicting the UCS and ETR in the testing phase are also shown The regression diagrams of the proposed hybrid RF models using the test set are shown in h) and the number of neurons in each hidden layer (Ne). The penalty parameter (Pc) and the RBF kernel parameter (k1) are the main parameters affecting the SVR model performance. The ELM model is a special ANN model with a single hidden layer, thus the number of neurons in this layer (Nn) can control the performance of the ELM model. The KELM model has similar hyperparameters with the SVR model, i.e., regularization coefficient (Rc) and the RBF kernel parameter (k2). After developing these four ML models, the performance indices of each model with the best hyperparameter combination are shown in 2 and VAF, and lower values of RMSE and MAE. Meanwhile, it is obvious that the LHSPOA-RF model is the best model to predict the UCS and the ETR of the novel aseismic rubber-concrete material in this study.Moreover, four common ML models named the BPNN, support vector regression (SVR), ELM and kernel-extreme learning machine (KELM) are developed to predict the UCS and the ETR of the novel aseismic rubber-concrete material and compare the predictive performances with the proposed models. For the BPNN model, the hyperparameters are the number of hidden layers . Furthermore, the comparison results of four common ML models and the proposed hybrid RF models showed that the LHSPOA-RF model is the best prediction performance among all models.The strength and energy absorption properties of aseismic concrete materials have a significance effect on tunnel stability when a tunnel is shocked by an earthquake and other dynamic impacts. To clearly investigate the above two aseismic performance indices of a novel aseismic concrete material, experimental tests and soft computation techniques are combined in this study. Based on the uniaxial compression test and impact tests, an improved pelican optimization algorithm (POA) using the Latin hypercube sampling (LHS) method and the Chaotic mapping (CM) method was proposed to optimize the random forest (RF) model for predicting the aseismic performance of this novel material. The prediction results demonstrated that the LHSPOA-RF model and CMPOA-RF model have better predictive performances than the general POA-RF model for predicting the UCS and the ETR, especially the LHAPOA-RF model with a more satisfying performance accuracy of RIn addition, rubber plays an important role in strength prediction and cement is the most important parameter for predicting the energy absorption property.This work indicates that the application of the intelligence models to the aseismic material performance is an effective and more simple method that does not lose accuracy compared with traditional experiment tests in the laboratory. However, the limitation of this combined method is the number of samples in the used database. More and more tested or monitored data should be added into the intelligence models’ development to improve the prediction accuracy in the further research.


Nanofluids substantially enhance the physical and thermal characteristics of the base or conducting fluids specifically when interacting with the magnetic field. Several engineering processes like geothermal energy extraction, metal casting, nuclear reactor coolers, nuclear fusion, magnetohydrodynamics flow meters, petrochemicals, and pumps incorporate magnetic field interaction with the nanofluids. On the other hand, an enhancement in heat transfer due to nanofluids is essentially required in various thermal systems. The goal of this study is to figure out that how much a magnetic field affects nanofluid flow in an enclosure because of a dipole. The nanofluid is characterized using a single-phase model, and the governing partial differential equations are computed numerically. A Pseudo time based numerical algorithm is developed to numerically solve the problem. It can be deduced that the Reynolds number and the magnetic parameter have a low effect on the Nusselt number and skin friction. The Nusselt number rises near the dipole location because of an increase in the magnetic parameter  Nanofluids are very eminent in many energy systems and play a crucial role in the heat transfer mechanism. Usual base fluids like alcohol, graphene, engine oil, and water possess a low competency to improve the heat transport rate. Therefore, the amalgamation of base fluid in the tiny sized solid constituents would improve the heat transfer rate . Ultimatve tubes . Variousve tubes ,7,8,9,10Flows involving magnetohydrodynamic effects have potential uses in fiber coating, plasma confinement, magnetic material processing industries, photochemical reactors, purification of crude oil, magnetic drug targeting, nuclear fusion, and many other fields. Investigations concerning MHD flows have been carried out by many researchers. Yang et al.  used theNanofluid flows through cavities with heat transfer characteristics under the magnetohydrodynamic effects have been extensively studied by numerous researchers because of their practical implementations in several areas of science and technology. MHD nanoparticles flow inside a lid driven cavity, under the impact convective conditions on boundary, was discussed numerically by Muthtamilselvan and Doh . The wal3O4) together with H2O in a cavity, under the entropy generation effect, was carried out by Mohammadpourfard et al. [The cavity flows have considerable effects on the heat transportation and thermal performance of many systems, and play an essential role in cooling and heating energy systems. Examples incorporate solar collectors, nuclear reactors, energy storage geothermal reservoirs, underground water flow, and boilers. Flows of different fluids within a cavity have been analyzed by several researchers. The flow of ferrofluid  has been adopted to simplify the nanofluid flow model. The tabular and graphical outcomes express the dominant effects of the preeminent parameters on the heat transfer and flow in the cavity filled with nanofluids. New vortices seem to be appearing in the flow field with the existence of a dipole in the vicinity of cavity.2O3 are considered nanoparticles, which have been used in the nanofluid.To examine the thermodynamic properties and flow characteristics of an incompressible and laminar nanofluid flow under the dipole influence, we formulated the governing equations using SPM, as follows:Here:x and y-axis, respectively.Where location .perature .All other terms have their conventional meanings.It is worth noting that the physical characteristics of the nanofluid are denoted by the subscript (nf).Boundary conditions:After removing the pressure term, we get the following:We use the dimensionless variables listed below:Now, Equations (4) and (6) imply that:The dimensionless parameters are portrayed in nf subscripts) given in Equations (1)–(4) will be analyzed using the relations described in [It is essential to state that the physical properties of the nanofluid –(10) have been iteratively solved with respect to the boundary conditions given in Equation (11). A pseudo-transient approach, which involves time as an iteration parameter, is employed to determine the numerical solution of the problem.For the numerical solution, we may incorporate central differences for the spatial derivatives, whereas a predictor–corrector-like approach may be followed for the time integration. With the superscripts representing the time level and the subscripts denoting the location of the grid point, the system of governing equations when discretized, as stated above, may be written as follows:nth time level to the (n + 1) level. Here, h and k represent the grid-spacing in the horizontal and vertical directions, respectively, where the time-stepping is represented by Finally, we have to numerically solve the following equations in order to determine the numerical solution of the problem:The pseudo transient approach can solve complex dynamical nonlinear problems in an efficient way. Pseudo time is a mathematical time function that accounts for the parameters involved in the dynamical problems. The objective of the pseudo time analysis is to take a collection of parametric data from a dynamical problem (as in the concerned problem) and to provide numerical outcomes. The solution algorithm is implicit pseudo-time dependent for which Equations (20) and (21) are linearized around time-level n + 1 to obtain the numerical solution. In this method, central differences are used to discretize the governing equations. After finding the stream vorticity function, we determine skin friction To appraise the precision of our numerical procedure, we solved the problem provided by Shih and Tan  by develh = 0.01.In addition, the average Nusselt number on the hot wall is correlated with the established results see in  develope2O3 are considered in the nanofluid. Furthermore, in our simulations, we set the value of We will look at the impact of preeminent factors like the Reynolds number o Pr=6.2 .In the present case, the Eckert number is presumed to be quite small  and base fluid (2OH) within an enclosure is presented in this work. The main purpose of this study is to examine that how much a nanofluid flow is affected by the magnetic field inside an enclosure due to the presence of a dipole. The single-phase model is adopted to characterize the nanofluid, and the governing partial differential equations are computed numerically. The results evidently reveal that The Reynolds number and the magnetic field give rise to the Nusselt number in the surroundings of the dipole.The new vortices also seem to be rotating in the alternating paths due to dipole movement.The magnetic field and Reynold number form more vertices near the dipole location.The imposed magnetic field shifts the thermal gradient around the dipole location.No significant change is found in the shear stress for The influence of Reynold’s number on the Nusselt number and The skin friction becomes more effective along the lower wall in the presence of the dipole.An inclusive computational analysis of the dipole interaction with the flow of nanoparticles (


TLS is nowadays often used for deformation monitoring. As it is not able to scan identical points in different time epochs, mathematical models of objects derived from point clouds have to be used. The most common geometric form to describe built objects is a plane, which can be described by four parameters. In this study, we aimed to find out how small changes in the parameters of the plane can be detected by TLS. We aimed to eliminate all possible factors that influence the scanning. Then, we shifted and tilted a finite physical representation of a plane in a controlled way. After each controlled change, the board was scanned several times and the parameters of the plane were calculated. We used two different types of scanning devices and compared their performance. The changes in the plane parameters were compared with the actual change values and statistically tested. The results show that TLS detects shifts in the millimetre range and tilts of 150″ (for a 1 m plane). A robotic total station can achieve twice the precision of TLS despite lower density and slower performance. For deformation monitoring, we strongly recommend repeating each scan several times (i) to check for gross errors and (ii) to obtain a realistic precision estimate. Temporary and permanent deformations occur in engineering structures due to natural and artificial forces. Our goal was to identify these deformations. In engineering geodesy, especially in the field of deformation and displacement measurements of structures, traditional surveying methods are usually used. Heights and vertical displacements are measured with high-precision levelling methods , while sTerrestrial laser scanning (TLS) is one of the most effective technologies for data acquisition in cases where 3D information with a high resolution is required. Laser scanners have, thus far, not been frequently used for high-precision engineering geodesy measurement tasks, such as deformation monitoring, since the technical specifications of most laser scanners do not fulfil the accuracy requirements in such applications . For theThe problem of non-identical points can be solved by adjusting simple geometric models based on the point clouds. Most of the constructed objects can be described or divided into smaller mathematically determined shapes such as planes, spheres, and spline surfaces.In the following section, we discuss how small plane changes, in terms of translation or rotation (declination) of the plane, can be detected by TLS.Geodetic monitoring was performed on the water barrier at a hydro power plant. The task was to detect the deformations of the object. The concrete flat-shaped wall was scanned in two time epochs. The point cloud was segmented to smaller areas. For each of them, the changes of plane parameters were investigated. However, what changes are permissible and when are they statistically significant? In this study, we focused on the actual ability of the terrestrial laser scanner to detect such changes. Therefore, the position changes of plane primitive represented physically by the board plane were investigated. We compared an actual terrestrial laser scanner (Riegl VZ-400) with a robotic total station (Leica MS50) featuring a scanning function.In a previous paper , we presThis question will be systematically examined in the following sequel. In this article, we highlight the developments in TLS systems that also allow the use of such systems in deformation monitoring. For a reliable analysis, it is important to know the displacement and inclination of the board and that the plane parameters are calculated from several iterations of the scan of the board in each position. This type of research is important because it provides additional information about the usability and reliability of the TLS system for studying deformations.Generally, deformations describe either geometrical changes in shape and dimension  or rigid body movements  (p. 705)The development of terrestrial laser scanners has substantially increased the importance of areal measurements in engineering geodesy. Among these, areal deformation measurement (ADM) techniques provide the opportunity to extend the observed region to a large portion of a structure instead of merely measuring a set containing a few discrete control points . PreviouTLS data have been used for various engineering applications, such as building information modelling (BIM) , surveyiTo ensure the metrical integrity of the laser scanner data for deformation analysis, it is important to independently evaluate the scanner’s performance within a calibration scheme. Tsakiri et al.  presenteAn estimated deformation field may be caused by errors in the point cloud, including general point cloud errors, registration errors, modelling errors, and cloud-comparison errors. Therefore, a deformation monitorable indicator (DMI) must be determined to distinguish deformation from errors in the point cloud. DMI also describes the minimum deformation that can be extracted from the point cloud to assess the capability of deformation monitoring .Due to the limited accuracy of scanners, the possibility of using TLS in deformation monitoring remains uncertain. To increase the accuracy of the results, the chosen parts of a monitored structure can be approximated by single geometric entities  using orthogonal regression. In this case, the position of a measured point (part of structure) is calculated from scanned points instead of a single measurement . ResearcRecently, researchers have explored the applicability of using TLS in a motor-vehicle-based mobile mapping system with a high degree of automation for cost-efficient deformation monitoring of anchored retaining structures along public roads . ScaioniAlthough individual sample points are low in precision and, therefore, preclude their use in deformation monitoring, modelling the entire point cloud may be effective for representing changes in the shape of a structure .For each scan of the board plane, the parameters were extracted. The mathematical model of the plane is as follows:For large datasets 0): there is no displacement, The null hypothesis (H1): displacement exists, The alternative hypothesis ;Setups with boards at incidence angles of approximately 0°, 40°, and 75° .The experiment consisted of 9 board setups:For the shift test, in each of the nine setups, we shifted the plane by the chosen value in the approximate direction of the plane’s normal. For the tilt test, in each of the nine setups, we tilted the plane by the chosen small angular value around the horizontal axis at the bottom of the board see .All other interferences and influences were reduced as much as possible.A terrestrial laser scanner, Riegl VZ-400;A robotic total station, Leica MS50.For this research, two scanning devices were used:The technical specifications of these scanners are listed in We sought to test whether any of the instruments would provide better robustness or stability and whether they would be able to detect smaller changes.For the shift test of the change detection in parameter g tripod . A BahcoFor setups with different incidence angles, the whole mount was rotated around the heart screw on the tripod table. For these setups, the changes were applied in the direction of the normal vector as desired and not in the direction of the measured distance from the scanner.For the tilt test to detect changes in normal vector inclination, the same wooden board was attached to a massive metal tilting table  with hinTo explain the results, we first plotted all values obtained from a single setup . Figure The upper three frames  present Vertical black lines designate the physical tilting or shifting of the board. The parameter values of ten repeated measurements are provided in each area.Each line colour corresponds to one of the plane parameters  of the board declination.The thick horizontal lines in each area  correspond to the mean values of the parameters in the area, while the thin horizontal lines indicate the standard deviation. Considering these figures, we sought to determine whether the positions of the thick lines in the first area (0″) were significantly different from their positions in the following areas , while always testing the difference between the initial position (0″) and each of the subsequent positions, and not between successive positions.d omitted (as shown in the lower-middle frame); for the shifting test, Statistical testing was used to produce the lower three frames in In the following section, we focus on the main results separately for the shifting and tilting tests.For this test, the board was scanned 10 times with both instruments in the initial position . Since the board was translated in the direction of the normal vector, we expected that only plane parameter In total, we used nine setups at three different distances and with three different incidence angles. Therefore, nine lines are plotted in each frame. The discussion on these results is in For this test, the board was scanned 10 times with both instruments in the initial position. Then, the board was tilted by a chosen value and scanned 10 times again , the middle frame shows the results of the three degrees of freedom test  in each epoch. In addition to gross-error detection, this method also allows the assessment of the precision of parameters adjusted from point clouds.The total station, despite having lower scanning density, provided precision approximately two times higher than the actual terrestrial laser scanner. For Riegl VZ-400, the average parameter precision was below 1 mm; for Leica MS50, the result was two times better: below 0.5 mm. This result was expected since the nominal specifications of the used instruments outlined the higher precision of the total station.Longer distances led to lower precision values for both instruments. Furthermore, in most cases, larger incidence angles led to lower precision.Some general conclusions can be deduced from For the tilting of the board, the perceived average accuracy for both instruments was between 20″ and 30″. This value corresponds to a tilt value of 0.15 mm per meter. The accuracy decreased with increases in both distance and incidence angles.For shifting the board translationally, the perceived average accuracy for Riegl VZ-400 was 0.4 mm and for Leica MS50, 0.1 mm. Significant changes according to distance or incidence angle were not observed.Accuracy describes the degree of conformity between the detected deviations and the actual values. For the given dimensions of the board, for both instruments used in the experiment, we can report the following  test. This might lead to the detection of significant changes too early . However, we can see from Lastly, we present the findings related to our main research question concerning the statistical significance of the detected changes:When using TLS to monitor deformations and detect changes, many influencing factors must be considered, such as the stability of the control points, the geometry of the georeferencing, the environmental conditions, and last but not least, the instrumental errors. In this study, we aimed to find out how small changes in the plane parameters can be detected by TLS between two successive measurements, given the same scanner orientation and the same external conditions. With specific instrumentation, we aimed to illustrate the limitations of the TLS in the field of deformation detection on a single primitive. Our work can also be representative of how experts using TLS for deformation monitoring should test their own measuring equipment to find out the limits of their own TLS measuring devices in terms of precision and accuracy.In addition to the threshold for detectable change, we also compared two scanning devices: a Riegl VZ-400 terrestrial laser scanner and a Leica MS50 robotic total station. In both the plane shift and plane tilt tests, we evaluated the accuracy and precision of the two instruments. Our experiments confirmed the superior accuracy and precision when scanning with the total station, except for tilting detection. The user, however, must also consider the tedious and slow scanning performance of such instruments.To conclude, the results indicate that through laser scanning of the object and plane adjustment through the point cloud, we are able to detect millimetre shifts of the plane and less than 1 mm per meter in inclination.Special attention should be paid to possible gross errors when scanning with actual TLS instruments. As well as avoiding the aforementioned start-up effects of TLS, we propose scanning multiple times since the time required for scanning is not as problematic as the benefits of such a procedure.


Robot-assisted technology is often used to perform endovascular catheterization surgeries, which generally depend on the flexible operability and the accurate force feedback of a robotic system. In this paper, an endovascular catheterization robotic system (ECRS) was developed to improve collaborative operation and haptic force feedback. A couple of operating handles were designed to maximize the use of the natural operations of surgeons on the master side, which is a flexible and ergonomic device. A magnetically controlled haptic force feedback structure is proposed based on hydrogel and solid magnetorheological (MR) fluid to offer a sense of haptic feedback to operators; this has potential influence on the field of force feedback. In addition, a unique tremor-reduction structure is introduced to enhance operating safety. Tracking performance experiments and in vitro experiments were conducted to evaluate the performance of the developed ECRS. According to these experimental results, the average translation-tracking error is 0.94 mm, and the average error of rotation is 0.89 degrees. Moreover, in vitro experiments demonstrated that haptic feedback has the advantage of reducing workload and shortening surgery completion time. The developed ECRS also has the benefits of inspiring other researchers to study collaborative robots and magnetically controlled feedback. Robot-assisted endovascular catheterization (EC) systems are attracting growing interest and attention due to the obvious drawbacks of traditional vascular interventional surgery (VIS), including prolonged X-ray radiation, high-intensity surgical stress and unmonitored surgical risks . In the Recently, robot-assisted EC surgeries, including the structure of the master–slave system, haptic force feedback, and tremor reduction, have been studied in a few major fields . FlexiblThe current related efforts of robot-assisted EC systems can be divided into two categories: the design of the robotic system and the guarantee of safe operation. For studies about the design of the robotic system, an incipient EC robot was proposed to deal with the problem of remote surgery based on the “Slave–Master” structure. Additionally, a smart material, MR  fluid, was proposed as the leading solution to providing flexibly controlled and effective haptic force feedback . In 7],,7], the In addition, an augmented endovascular robotic system using conventional surgical tools was created to generate feedback and ensure operation safety , and a tFocusing on the research of haptic force feedback, Lai W. et al. designed a tendon-sheath force sensor to measure the compression force with error of 0.178 N and sensitivity of 34.14 pm/N , but its® robot, MagellanTM robotic system, and AmigoTM surgical robot, have been developed to assist with VIS in hospitals. Unfortunately, these commercial robots cannot realize force feedback or achieve precise haptic force feedback.Thus far, numerous commercial robotic systems, such as the CorpathWith the aims of safe robot-assisted surgery, high-precision force feedback, and ergonomic design for robot-assisted surgeries, An endovascular catheterization robotic system (ECRS) using collaborative operation with magnetically controlled haptic force feedback is developed in this paper. This system makes it possible to follow doctors’ natural operating habits and provides haptic feedback when conducting surgeries; it has the potential application value of reducing workload, improving the surgical environment, shortening surgery time, and enhancing operating safety for surgeons. Compared with other robotic systems in the field of VIS, our ECRS has two innovative advantages in manipulating robot-assisted surgery. Firstly, the collaborative operation master device based on a couple of handles enables maximum replication of the physician’s operation. Secondly, we proposed the magnetically controlled haptic force feedback molded by solid MR fluid and the smart material hydrogel, which is a new case in cross-disciplinary application. This also has potential application value in the fields of haptic feedback, controlled clamping, and biological self-healing.The remainder of this article is organized as follows: This section presents the mechatronics of our developed ECRS. The ECRS is a teleoperated surgical system. It is made up of a master haptic device, a slave manipulator-robot, and control mechanism. A detailed description of the master haptic device, slave manipulator-robot, and system control architecture are given in this section. The master device is mounted in the control room (master side) to be operated by surgeons. Correspondingly, the slave manipulator is installed on the operating bed or independent robotic arm (slave side) to deliver surgical instruments and detect necessary force and position information. The system control mechanism is used to exchange information between the master device and slave manipulator.(1)Guidewire operating handle (GOH): In order to capture the radial motion of the input guidewire, an encode sensor  is mounted to the right of the GOH. A laser sensor  installed in this handle has the ability to detect the real-time axial motion. At the same time, the structure of the haptic force feedback will provide specific resistance for operators when manipulating the input GOH. A detailed introduction of haptic force feedback will be presented in (2)Catheter operating handle (COH): With the aim of collecting the motion information of the input catheter, we utilize a high-level integrated photoelectric sensor (PS). This kind of PS includes two photoelectric measuring cells, which are perpendicular to each other. The movement of the handle rod drives the trackball into rotation, then two photoelectric measuring cells detect the motion signal. The biggest advantage of employing the PS is that it can simultaneously capture translational motion and rotational motion, which will greatly shorten the length of operating handle. Meanwhile, reset structure II, mounted on the screw II, is also able to cut down the distance of the COH. Lastly, the catheter operating position (COP) for surgeons is marked with a blue circle  control board, which can capture operations from the master side and drive the movements of the guidewire and catheter on the slave side. Additionally, the force signal and position signal of the slave side can be detected in real-time, and the vision feedback is provided by a network camera . On the master side, the monitor information is displayed on a screen, which can guide the doctor’s treatment process. The system control architecture developed for the ECRS is shown in Considering the core research challenges of EC robots, the haptic feedback on the master side and the force detection mechanism on the slave side will be presented in this section. The purpose of haptic force feedback is to improve the robotic environment by providing a surgical-resistance sensation to operators. Meanwhile, the collaborative operation process is introduced for surgeons when conducting surgery using the proposed master haptic device.In order to realize the haptic force feedback on the master side, we propose a magnetically controlled haptic force feedback structure based on a solid magnetorheological (MR) material and hydrogel rubber. This section describes the details of the implementation of haptic force feedback in our study. The novel implementation of this method consists of component preparation, a molding process, and structure assembly, which are introduced as below.(1)Component preparation: Earlier research by our team adopted MR fluid to generate haptic force feedback [TM, 00-20, Macungie, PA, USA) includes mixture A and mixture B, which need to wait for their pot-life of 30 min. The mixed liquid should also be prepared before the molding process. feedback ,7. This (2)Molding process: After the process of preparation, four steps are proposed to build the magnetically controlled hydrogel (MCH), which will be employed to offer haptic feedback. The detailed molding process and generated samples are shown in (3)Structure assembly: This part is the last procedure to build the complete haptic force feedback structure. It is important to assemble the MCH with 3D-printed parts, which should be mounted under a magnetic environment. The underlying principle of “haptic device” is frictional resistance generated by contact between the MCH and a nonmagnetic rigid rod. As shown in In our proposed master haptic device, the reduction in operational tremors is a highlight that cannot be ignored. The appearance of hand tremors in VIS will directly affect the accuracy of the translation motion and the rotation motion of the master–slave robot. Hence, we designed a related structure to reduce operating tremors. We designed a restriction track with a length of 10 cm to deal with unknown tremors, which are generated in catheter operating handle (COH). In addition, the guidewire operating handle (GOH) adopts two ball splines  to suppress tremors of the hand, and also has the function of supporting the COH. Ball splines are famed for their small resistance and smooth running, based on the special structure of the recirculating balls and track, which are shown in Collaborative operating is vital for surgeons when conducting interventional surgeries. In this study, the coaxial design of the handles and the separate structure of the catheter handle and the guidewire handle enable collaborative operations to be performed in accordance with the surgeon’s natural surgical method. The collaborative operation mechanism is exhibited in Force detection on the slave side is an important issue, and can capture real-time force information during surgery. This detected force can also be used for haptic feedback of the master side. Two load-cells mounted on the slave manipulator-robot detect the proximal force in the developed ECRS. As shown in This section describes the four types of experiment that were conducted to verify the performance of the developed ECRS. The purpose of experiment I was to establish a polynomial relationship between the magnetic field and the generated haptic force. Experiment II was used to evaluate the accuracy of the translation and rotation motion in the master haptic device. Experiment III was adopted to build the tracking performance. Lastly, we manipulated this ECRS to insert the guidewire and catheter into an EVE human model, described in experiment IV, which can clearly demonstrate the performance of the overall system.i is the value of applied current; m represents the value of magnetic density.In order to build the mathematical model between haptic force and the magnetic field, the experimental set-up was calibrated. The results for experiment I are displayed in We organized three kinds of evaluation experiments to test the measurement accuracy of the proposed master operating device. The details of the experimental setup for translation and rotation are shown in In the rotation performance evaluation experiment (a), we used a rigid coupling to connect the catheter handle and the rotary axis of the sliding platform, to ensure absolute coaxial rotational motion. According to doctors’ natural surgical actions, the catheter operating handle was rotated using both counterclockwise and clockwise operations at a relatively gentle speed to reduce operation errors. We obtained the rotation accuracy by comparing the measured rotation angles of the encoder and the PS.In the translation performance evaluation experiment (b), we placed the left end of catheter operating handle so that it directly contacted the linear rigid shaft with gears , the guidewire operating handle (GOH) and the black linear rigid shaft of the sliding platform were put on the same axis. The receiver end (white receiver piece) was printed with a polylactic acid (PLA) material to reflect the laser light emitted by the laser sensor. The purpose of this experiment was to test the linear-motion-detection accuracy of the guidewire operating handle using a laser sensor. The measurement data were processed using an Arduino Mega 2560 and monitored on a computer. It is worth explaining the reason for only conducting a linear accuracy experiment for the GOH; due to the guidewire handle also using an encoder sensor see in  to measuThe experimental results for the accuracy evaluation of the master operating handles are shown in The accuracy result for experiment (c) highlights a lot of trembling moving data points. This is because the designed receiver end is a 3D-printed PLA suspended structure instead of a rigid material. During the process of translation movement, the receiver end incurred a small range of front-to-back shaking. The pink line is the movement measured by the encoder; the green line is the movement measured by the LS; and the purple line is the error. After calculating the results in experiment (c), the minimum error is less than 0.2 mm, and the average translation error is 3.24 mm.In order to verify the tracking performance between master haptic device and slave manipulator-robot, we designed this part. By comparing the moving distance and rotation degrees detected on both the slave side and the master side, the tracking performance of this system was clearly demonstrated. In this experiment, we set the amount of movement in master device to 12 mm (corresponding to 1000 pulses for the encoder), and the theoretical movement value of the manipulation robot to 36.34 mm. For the rotation tracking performance in this part, we set 180 degrees as the input signal of the master device. The measurement rotation range of the slave side was 0 to 360 degrees. Each kind of experiment was conducted five times.The experimental results for tracking performance are shown in To further verify the actual surgical performance of this developed ECRS, a trans-parent endovascular evaluator  human model was adopted in this experimental part. A pressure pump  was used to continuously inject simulated blood into the EVE human model, which is a very realistic surgical operating environment. In addition, we utilized a monitoring interface located on the slave side and displayed on the master side, to monitor the surgical status for insertion and extraction in real time. The details of the in vitro experimental setup are shown in The in vitro experiment results are shown in From the experiment results in In addition, we invited six trialists to operate this developed ECRS in the in vitro experimental environment. At the beginning, training in the use of the operation method and attention paid to the items were necessary, since the trialists had different levels of medical operating knowledge. The force was measured using a load cell when the trialists operated this system on the EVE model. We counted the maximum force values in guidewire-inserting experiments of these six trialists; these values are shown in From An ECRS is developed in this paper for robot-assisted vascular interventional surgery. This system makes it possible to follow doctors’ natural operating habits, and provides haptic feedback when conducting surgeries; it also has the potential application value of reducing workload, improving surgical environments, shortening surgery time, and enhancing operating safety for surgeons. Compared with the EC robots of other researchers, the proposed ECRS presents three significant contributions: Firstly, a cooperating master device based on two different independent handles is proposed, which can accurately drive the movement of the catheter and the motion of the guidewire; secondly, a unique structural design that can reduce operation tremors was adopted in the ECRS; and thirdly, a magnetically controlled haptic force feedback structure was designed based on hydrogels and magnetorheological (MR) fluids, which also has potential application value in the fields of haptic feedback, controlled clamping, and biological self-healing.Regarding the tracking performance of this system, the average error of translation was 0.94 mm and the average error of rotation was 0.89 degrees. Despite our maintenance and cleaning before conducting the experiments, these errors still existed. This level of tracking error was generated by the unavoidable time loss in the slave manipulator and the precision deviation of mechanical manufacturing. Furthermore, due to the specialty of surgical instruments, the force information on the guidewire and catheter were distinctly different. The guidewire is hydrophilic, with easy bending of the head. Hence, the force of the guidewire was relatively small, usually less than 0.5 N. In contrast, the force of catheter was quite large due to the harder material, the friction between the guidewire and catheter, the interaction between the blood and the catheter body, and the contact between the vessel wall and the catheter. In particular, the catheter sheath for securing the surgical insertion position had a kind of necessary clamping force, which was a major influencing factor for the measurement of catheter force. Generally, the largest force value of the catheter was over 1.5 N. In addition, another influencing factor was whether or not trialists had operating experience. Skilled operation directly affected the smoothness of the manipulating procedure, surgery completion time, and the force data measured by the force sensor. Consequently, different types of subjects will be considered in the next robotic study and deep research.In this paper, a developed endovascular catheterization robotic system (ECRS) with magnetically controlled haptic force feedback was presented, to complete collaborative operations and also to provide critical haptic feedback. Using the two operating handles to manipulate the catheter and guidewire, the ECRS is able to reproduce doctors’ natural skills. The ability to reduce operating tremors enables more accurate movement and motion data to be captured on the master side. Most importantly, we invented a magnetically controlled haptic structure based on solid MR and hydrogel, which can offer stable force feedback to operators. Our experimental results prove the feasibility of the developed ECRS, as well as its good performance in robot-assisted surgery.Moreover, as one of potential advantages of the developed ECRS, the collaborative operation master device will have the effect of inspiring researchers to use master–slave robots in other fields, such as rehabilitation, ophthalmology, deep sea tasks, and air exit operations. Furthermore, the haptic force feedback with the function of magnetic control also has benefits in navigation, haptic perception, and controlled self-healing materials. In the future, research on multifunctional robotic systems and more accurate and smooth haptic force feedback will be considered and studied.


Stability of timing and force production in repetitive movements characterizes skillful motor behaviors such as surgery and playing musical instruments. However, even trained individuals such as musicians undergo further extensive training for the improvement of these skills. Previous studies that investigated the lower extremity movements such as jumping and sprinting demonstrated enhancement of the maximum force and rate of force development immediately after the plyometric exercises. However, it remains unknown whether the plyometric exercises enhance the stability of timing and force production of the dexterous finger movements in trained individuals. Here we address this issue by examining the effects of plyometric exercise specialized for finger movements on piano performance. We compared the training-related changes in the piano-key motion and several physiological features of the finger muscles  by well-trained pianists. The conditioning demonstrated a decrease of the variation in timing and velocity of successive keystrokes, along with a concomitant increase in the rate of force development of the four fingers, but not the thumb, although there was no change in the finger muscular activities through the activity. By contrast, such a conditioning effect was not evident following a conventional repetitive piano practice. In addition, a significant increase in the forearm muscle temperature was observed specifically through performing the plyometric exercise with the fingers, implying its association with improved performance. These results indicate effectiveness of the plyometric exercises for improvement of strength, precision, and physiological efficiency of the finger movements even in expert pianists, which implicates that ways of practicing play a key role in enhancing experts’ expertise. Conventional musical education and training, however, may emphasize the importance of quantity of the practice4 and subjective experience of trained teachers and performers, due to a lack of evidence proving effectiveness of individual ways of musical practicing5. In contrast, most of training and education in sports are built upon accumulated evidence through the development of sports science, which has contributed to breaking records over decades8. Following a similar perspective, musical performance requires reproducible and quantitative knowledge on the effectiveness of music education and training specialized for musicians who are required to perform highly dexterous sensorimotor skills in no way inferior to athletes5.Musical performance represents one of the most skillful motor behaviors, which typically requires years of extensive musical training from childhood9. While rhythmic variation of successive piano keystrokes in practicing improved maximum rate of keystrokes and altered finger muscular activation patterns in piano playing, there was no change in the rhythmic accuracy of the keystrokes following such a differential learning. Non-invasive brain stimulation using the transcranial direct current stimulation also improved fine control of the finger movements in untrained individuals, but not in trained pianists10. These results highlight difficulty of improving precision of repetitive finger movements in trained pianists, although a recent study discovered a rare case of achieving it through a specialized somatosensory training with a haptic device11.One approach to discover the optimal way of practicing is to compare effects of different ways of practicing on the sensorimotor skills. For example, a previous study examined effects of variation of the temporal structure of piano practicing on neuromuscular control of the sequential finger movements in pianists12. Previous studies investigating this exercise have focused mainly on fast, powerful movements of the lower extremities, such as sprinting13 and vertical jumping14, and have revealed significant reductions of muscular fatigue due to a decrease in the duration of forceful contraction compared to resistance exercises that maximally stretch the muscle spindles to the same degree12. Post-activation performance enhancement (PAPE) has been proposed as a putative physiological mechanism underlying the short-term improvement of the performance due to an increase in rate of force development (RFD) following some physical training such as not only high-intensity resistance exercises but also plyometric training15. However, evidence for the effectiveness of the plyometric exercises has been limited primarily to the lower extremity, with only a few studies in the upper extremity such as the shoulder16, but none in the forearm and hand that are different from the lower extremity in terms of neurophysiological and biomechanical architectures. Also, it has not been known whether the plyometric exercises enhance fine motor control  of trained individuals such as musicians. However, the increased force production capacity by the plyometric-like exercise let us postulate enhancement of precision of force production, due to a negative relationship between the force production capacity and signal-dependent noise in the motor commands17. In addition, a previous study also reported enhancement of movement accuracy through the plyometric training in archery player18.Plyometric exercise has been known as one established training in the field of sports, which consists of a quick succession of eccentric and concentric contractions of the targeted muscle20 and muscular activities21. Since it has been pointed out that changes in performance due to PAPE are supported mainly by elevation of muscle temperature15, and since its time course has been shown to accompany changes in motor skill23, muscle temperature was measured throughout the course of time before, during, and after the conditioning in this study. While several studies have investigated physiological mechanisms of piano performance and practicing25, there has been no study assessing the skin and muscular temperature of the finger muscles during piano practice. The present research will therefore provide performers and instructors with a basis for the application of evidence-based practice methods and conditioning regimes.The goal of the present study is to address effects of plyometric exercises on dexterous finger movements while trained pianists play the piano. To this aim, we assessed the time-varying trajectory of the vertical position of the piano keys, key-depression force, and finger muscular activities during the repetitive keypresses before and after the conditioning, based on previous findings of the relationship of pianistic skills with force exertion patterns12, the present study did not make any changes in the training protocol between them, because the fingertip exercise does not require large force production as compared to the lower extremity movements. In accordance with the Declaration of Helsinki, the experimental procedures were explained to all participants. Informed consent was obtained from all participants prior to participating in the experiment. All procedures were approved by the ethics committee at the Sony Corporation.Twenty-six pianists participated in the experiment . All of them had undergone intensive piano training and formal musical education at music conservatories and/or privately for > 14 yr. The pianists were randomly classified into two groups (i.e. thirteen pianists in each group in a gender-matched and age-matched manner) undergoing different conditioning tasks  was used in the experiment to collect data representing the timing, pitch, and velocity of the individual key presses and releases (i.e. MIDI information) with a custom-made LabVIEW  program. The instrumental sound was elicited via a headphone attached on the participant’s ears. The surface electromyography (EMG) system with two sets of wirelessly connected electrodes  was connected to a laptop through an analog-to-digital board . Each electrode was placed on the muscle belly of the extensor digitorum communis (EDC) and flexor digitorum superficialis (FDS) of the right hand. The EMG signals were amplified, band-pass filtered (10–500 Hz), and sampled at 1 kHz using LabVIEW. As with EMG, a custom-made force sensor connected to an analog-to-digital convertor was used to measure the force when each finger was pressing down the sensor. A high resolution position sensor system was mounted on the bottom of the key-bed15. In the pre-test and post-test sessions, participants were asked to perform two tasks: the piano test and finger force production test. At the beginning of the experiment, the isometric maximal voluntary contraction (MVC) was asked to be performed at the EDC and FDS to calculate %MVC during the task performance in a manual maneuver. Participants pressed down the four adjacent keys of the keyboard with all 2–5 fingers simultaneously for 1 s as strong as possible for assessing the MVC of FDS. During the measurement of MVC of EDC, participants pushed up the experimenter’s hand that was put on the participant’s hand with the back of all of the 2–5 fingers (i.e. extending the fingers) simultaneously as strong as possible for 1 s. The MVC assessment was performed twice for each of these two muscles. The maximum amplitude of the root-mean-squared EMG signal was calculated for each trial, and the larger value among the two was adopted as MVC.The experiment consisted of three successive sessions within a single day: pre-test, conditioning, and post-test. In addition, the post-test session consisted of three trials with a break in between; 0 min, 10 min, and 25 min after the conditioning, so as firstly to assess the effects of conditioning and its retention, and secondly to infer whether PAPE or PAP are candidate physiological mechanisms of the present conditioningFor the piano test, participants played the melody designated on a test score see Fig. A right w15 as short as one used in the present study.For the finger force production test, the elbow and wrist were immobilized on a table, and only the fingers were used to press the force sensor in a manner displayed on the musical score see Fig. A. As in In the conditioning session, participants were asked to perform the conditioning task with the right hand in an instructed manner that differed between the groups. Participants in the main group were instructed to perform a plyometric-like exercise with the piano 40 times in a manner displayed on the score  of the inter-keystroke interval (IKI) of two successive strikes was used as a variable representing stability of the tempo, whereas the CV of the keystroke velocity was used as an index representing the loudness stabilityData of the finger pressure and key motions were cut for each press/keystroke as epochs according to a threshold , which was used for time normalization of the epochs. These data were averaged across the epochs for smoothing, and the diff function in MATLAB (Mathworks Inc.) was used to compute the first and second derivatives of the vertical position of the key. The maximum value of each waveform was used for the subsequent analyses.The EMG data were bandpass filtered at 10–250 Hz in an offline manner to remove artificial high-frequency noise and movement artifacts with MATLAB using signal processing toolbox. The same time-index was used for time normalization of the EMG signals to temporally align each epoch with the time normalized force and key motion.28 only in the case of significance with correction for multiple comparisons (p < 0.05).A two-way mixed-design ANOVA (independent variables: Group and Condition) or three-way mixed-design ANOVA  was run as needed using ez package in R (open source). Here, “Condition” has four levels , whereas “Group” has two levels (i.e. two different sets of training). If Mauchly's sphericity test was necessary, the Greenhouse–Geisser correction was performed. Post-hoc tests were performed using Benjamini and Hochberg correction for multiple comparisons_IKI = 0.321, p_vel = 0.976), whereas those in the main group was significantly decreased from the pre-conditioning to the 0 min condition .Figure Figure In order to identify factors associated with the aforementioned results, we investigated effects of the plyometric activity on RFD during the finger force exertion in the finger force production test. Figure Figure Figure 11.The present study found that the plyometric conditioning targeting the finger flexor muscle was effective as exemplified by a decrease of the variability of both timing and velocity of the keystrokes when performing a pianistic task that requires loud and fast tone production. On the other hand, such a significant effect of the conditioning on the accuracy of movement was not observed following the activity with repetitive piano keystrokes that did not involve the plyometric-like muscular contraction (i.e. a control group). The contrasting group difference indicates that the plyometric exercises used in this study enhances precision of the finger movements in fast and forceful repetitive piano keystrokes, which has been difficult to be achieved in previous studies. Interestingly, the spatiotemporal features of the finger muscular activities did not change following the plyometric exercise for both FDS and EDC, whereas the finger muscular but not skin temperature was elevated as the plyometric exercise was being performed. This suggests physiological changes at the finger muscles by the plyometric activity. Together, these results indicate that the plyometric exercise has potentials of further improving well-trained performance skills of pianists who underwent extensive training and have difficulty of improving their skill through conventional training (i.e. ceiling effect)17. It is therefore plausible that the strengthening effect of the plyometric exercise on the finger muscles aided in reducing signal-dependent noise in the motor commands issued into the muscles and thereby decreased the variability of the exerted force. Interestingly, the muscular activation was not augmented through the conditioning (i.e. EMG amplitude), even immediately after the conditioning before taking rest (at 0 min) and its subsequent period following the conditioning, although the force production was increased. This indicates that the target force can be produced with reduced finger muscular activities of the finger, implicating improvement of physiological efficiency in the finger force production. This can play a role in preventing muscular fatigue and/or development of overuse syndromes through piano practicing, in addition to enhancement of timing and force precision in piano performance.To evaluate the conditioning effect on the finger motor functions, we assessed RFD in the isometric finger force production for flexion. Specifically following the plyometric-like piano exercise, RFD was increased for each of the four fingers that underwent the activity. A lack of any conditioning effect at the thumb that did not perform the plyometric conditioning and at all fingers that underwent the conventional repetitive practicing supports the idea that the enhanced ability of the finger force production resulted from this plyometric activity. Similarly, the conditioning effect was also evident for the maximum acceleration of the piano key-depression, which was correlated with improvement of precision of timing and velocity in the piano keystrokes. One possible explanation for the enhanced piano performance is a negative physiological relationship between the muscular strength and variability of the force production30, which explains why the muscle temperature was elevated along with the increase in RFD of the skeletal muscles in both present and previous studies32. In other words, the increase in RFD may be due to an increase in the chemical reaction rate during muscle contraction as the muscle temperature elevates, which has been observed as an increase in the muscle power output in passively warming  hands33. This can be a potential reason why the RFD was increased through the plyometric activity.As one putative physiological mechanism behind the effect of the plyometric conditioning on the force production ability, we found elevation of the finger muscular temperature but not of the skin temperature specifically following this conditioning. Muscle contraction begins with the release of calcium ions from the sarcoplasmic reticulum into the myofibrils, which binds actin and myosin heads (cross-bridges) and then consumes energy from the ATPase reaction for contraction. Previous studies have shown that the cross-bridge cycling rates for muscle contraction are affected largely by the temperature-dependent myosin-ATPase reaction11. These two phenomenon are considered to be different with respect to their temporal dynamics  and to muscle temperature change (i.e. only PAPE but not PAP accompanies it)15. It has been shown that plyometric exercise can induce PAPE as a conditioning exercise not only in the lower limb but also in the upper limb at the short force production rather than resistance exercises with high and lasting long force production34. In the present study, we used plyometric conditioning for the finger muscle, which demonstrated concomitant changes in the finger muscular temperature along with the plyometric-related activity, and eventually an increase in the RFD at the four fingers that underwent the conditioning. Also, the increase in RFD and motor performance lasted 25 min, which also supports PAPE. Several remarkable effects of skill improvement by PAPE has been demonstrated in tasks especially with high-speed force exertion such as sprinting and jumping. Piano performance in this study similarly require high-speed movements and strong muscle contractions of more than 10 times per second, and the results indicate that the application of PAPE is highly compatible with such movements. This observation suggests that selective application of plyometric exercises to the finger extrinsic muscles induced PAPE, which may underlie the improved motor skills in piano performance. Several alternative explanations for the skill improvement still remain, which include that motor learning with a modified rhythm of the target task optimized muscle coordination of performance as was observed in a previous study5, or that participants acquired a different way of keystrokes toward approaching the key surface through the activity, despite instructions to keep the fingers contact with the key throughout the performance.The phenomenon of improved motor performance following a conditioning exercise is called PAPE, which is recently proposed to distinguish it from conventional Post Activation Potentiation (PAP) due to Myosin Light Chain PhosphorylationThere are several limitations in the present study. First, to infer the physiological mechanism of the present conditioning effect, it is necessary to assess chemical changes within the muscles through the activity and neuroplastic changes in the primary motor cortex and spinal cord by means of non-invasive brain stimulation techniques. In future studies, it is also necessary to record activities of the intrinsic hand muscles and the other extrinsic muscles in order to uncover the entire physiological mechanism of the plyometric activity. Second, it is necessary to evaluate whether the plyometric activity effect on the finger movements has any gender-wise difference, because previous studies investigating the plyometric conditioning with the lower extremity found a differential effect between males and females, which should be also tested with the upper extremity. Third, the effect of different protocol and/or intensity of the plyometric conditioning should be systematically investigated  in order to optimize the conditioning effect. Fourth, although the present study focused on PAPE as a putative mechanism of effects of the plyometric exercise on the motor performance, other candidate mechanisms should be also studied such as changes in the intracortical functions of the motor cortex and muscle condition such as muscle water contents or degree of fatigue. Last but not the least, the present study did not fully validate the application of plyometric activity to the finger due to a lack of any previous study of its application to the same body portion. However, we found indirect evidence of PAPE through the measurement of muscle temperature, which can be considered as an indirect physiological evidence of the plyometric activity.


Cryptococcosis is a fungal infection that causes serious illness, particularly in immunocompromised individuals such as people living with HIV. Point of care tests (POCT) can help identify and diagnose patients with several advantages including rapid results and ease of use. The cryptococcal antigen (CrAg) lateral flow assay (LFA) has demonstrated excellent performance in diagnosing cryptococcosis, and it is particularly useful in resource-limited settings where laboratory-based tests may not be readily available. The use of artificial intelligence (AI) for the interpretation of rapid diagnostic tests can improve the accuracy and speed of test results, as well as reduce the cost and workload of healthcare professionals, reducing subjectivity associated with its interpretation. In this work, we analyze a smartphone-based digital system assisted by AI to automatically interpret CrAg LFA as well as to estimate the antigen concentration in the strip. The system showed excellent performance for predicting LFA qualitative interpretation with an area under the receiver operating characteristic curve of 0.997. On the other hand, its potential to predict antigen concentration based solely on a photograph of the LFA has also been demonstrated, finding a strong correlation between band intensity and antigen concentration, with a Pearson correlation coefficient of 0.953. The system, which is connected to a cloud web platform, allows for case identification, quality control, and real-time monitoring. Cryptococcosis is a life-threatening invasive fungal infection, with mortality ranging between 41 and 61%, especially in people living with HIV (PLWHIV) with meningitis being the most serious of its multiple manifestations. However, it has also been described in other immunocompromised hosts and as well as in people without known risk factors. An estimated 152,000 cases of cryptococcal meningitis occur each year, most of them in sub-Saharan Africa ,4.The cryptococcal antigen lateral flow assay  is a point-of-care test (POCT) with sensitivity and specificity >99% and 98% respectively . MoreoveThe widespread availability and use of smartphones have powerful implications for digital and mobile health care. The use of these devices in conjunction with POCTs would offer tremendous potential for improving the access to diagnosis, particularly in low-resource countries ,7. MobilThe aim of this study is to describe, as a proof of concept, the use of an AI algorithm embedded in a mobile app able to read CrAg LFA and interpret whether the result is positive, negative, or invalid in an objective and automatic manner. Moreover, we also determine if the proposed system is able to quantify the signal test intensity of the CrAg LFA which in an ideal situation could be used for the characterization of the syndrome as well as for the follow-up of the diseases after the treatment initiation.The proposed AI-assisted system for POCT result interpretation and reporting is presented in Cryptococcus antigen concentrations (ranging from 0.25 to 5000 ng/mL) prepared from the positive control provided by the kit as well as negative controls (no CrAg) were tested in duplicate during at least three different days with the CrAg LFA . All dilutions were performed in standardized human sera . Some pictures for some concentrations were taken on a fourth experiment as well as some concentrations were photographed more than two times, for different reasons, which means, the pictures set was not uniform for the 53 antigen concentrations tested.Fifty-two To assess the variability, each POCT was digitized and photographed, at least twice, by two different smartphone models with different technical capacities. One of the smartphone models is considered to be low-mid range (Motorola Moto E6), while the other is considered to be upper-midrange . Both devices are equipped with a ≥12 MPx camera.In total, 361 CrAg LFA were digitized, forming a set composed of 1500 images. All photographs were obtained using an artificial light source of approximately 6000 K neutral temperature.To generate the ground-truth which means to annotate the result of every LFA to build the training and validation sets of the AI algorithm, each POCT was visually interpreted by, at least, two different observers and classified as positive or negative. In those cases where there was a discrepancy between the two observers, a third one decided which was the final result after a careful reading of the questioned picture.To evaluate the quantitative readout algorithm, only 318 LFAs were considered resulting in a database that ensures that all concentrations are equally represented, with a total of 1272 images (53 CrAg concentrations × 2 times × 3 different days × 2 pictures × 2 mobiles = 1272 images).All POCTs were digitized using the TiraSpot mobile app . To take a correct picture of the POCT, TiraSpot displays a mask with the exact geometry and morphology of the CrAg LFA. Once the picture is taken, the app shows the image asking the user to confirm a correct acquisition . Configuration of the app can be freely adapted to the specific needs of the health system and can include any other relevant data required from a simple test determination to many variables to fill an observational database. The system can work without Internet access and once the device is connected all the information is uploaded to the cloud database.The AI algorithm was designed to interpret the test as positive, negative, or invalid. Once the valid picture of a CrAg LFA strip was taken and approved by the user, the algorithm pre-processes the original photograph by cropping the image to extract only the area where the control and test bands are, discarding the rest of the zone. This cropping is carried out based on the position that the LFA strip has in the mask presented to the user. A successful cropping process is dependent on a correct alignment between POCT and masks at the time of taking the photograph. Then, image normalization and contrast enhancement techniques are applied to the cropped image to highlight the faint bands and increase sensitivity. Finally, the processed image is introduced into a convolutional network (MobileNet V2 ) to predCryptococcus antigen concentrations (ranging from 0.25 to 5000 ng/mL) we decided to see if there was any correlation among the different concentrations and the signal intensity of the positive test in the LFA strip. An image analysis pipeline was developed to identify control and test lines of CrAg LFA and quantify their intensities. Since small variations in illumination intensity  and color temperature  can affect the intensity and appearance of POCT lines, we applied brightness and color correction techniques to the images. This correction makes the quantification process robust against variations introduced when using different lighting scenarios or different mobile models.As we tested fifty-three Once the image is pre-processed, the region of interest of the POCT result window is automatically detected and cropped using computer vision methods. With this purpose, we first detect both the upper red and lower blue areas of the CrAg LFA. Once these color areas are segmented, we identify the region of the result window, which is finally cropped. This cropped image is converted to grayscale and a one-dimensional signal profile is calculated as the average intensity along the short axis of the image. Then, the profile background is estimated (by using the asymmetric least squares smoothing method) and corrected, for normalizing among different ambient lighting conditions see . ControlRegression modeling was used to explore the relationship between normalized test band signal intensity obtained by the quantification algorithm and CrAg concentration.Regarding the qualitative readout algorithm, the image dataset was randomly split so 2/3 of the available images were used for training the algorithm, while the remaining 1/3 of the images were used for validation purposes. To generate an independent validation set we ensure that pictures taken from the same LFA were not used for both training and validation. The performance of the AI algorithm for qualitative LFA result interpretation was assessed in terms of sensitivity (SN), specificity (SP), the area under the ROC curve (AUC), and the overall accuracy (ACC) in the validation dataset, by comparing the visual interpretation (consensus among different observers) and the AI predictions. The mean, standard deviation, and 95% confidence intervals (CIs) were properly calculated. The DeLong test  was usedOn the other hand, the regression model that relates the signal intensity of test lines and antigen concentration was evaluated by calculating the Pearson correlation coefficient (r).Of the 1500 images used for training and validating the algorithm, a total of 29 images needed to be reviewed by a third observer due to a disagreement between the two initial observers. All of these images corresponded to CrAg LFAs inoculated with low CrAg concentrations (≤6 ng/mL). In all but one of these images, the third observer decided that they were positive although the test band was very faint being hardly visible. Of the 29 images that required the intervention of a third observer, 20 of them belonged to the training dataset, while the remaining 9 belonged to the validation dataset.The independent validation set  was composed of 502 images obtained after reading 120 different POCTs from the total 361 POCTs included in the study. As stated in the material and methods section, each POCT was photographed by two different smartphone models . The POCTs used for evaluation were different from the ones used for training the algorithm.p-value = 0.93). The confusion matrix, as well as the POCT photographs of discrepancies between visual interpretation and AI predictions, are shown in The performance of the algorithm  for the automatic reading of the CrAg LFA is detailed in Additionally, it was observed that out of the nine evaluation images where there was a discrepancy between the two observers, the AI correctly predicted the outcome and agreed with the third observer in eight out of nine cases. This fact proves that the algorithm is indeed able to provide an answer that could reduce the variability and discrepancy between observers.The AI algorithm was integrated into the acquisition mobile app enabling a real-time execution of the model (AI model runs on the mobile itself and no Internet connection is required). The user obtained the result in 121 ms (95% CI [120–123]), demonstrating that the AI App feeds back to the user at the time of image acquisition. The We included 318 digitized CrAg LFAs for the quantitative assessment to ensure the 53 concentrations were equally represented, which means the analysis of two replicates for each concentration during three different days. All replicates were photographed twice by two different smartphones counting a total of 1272 images (24 images per concentration).Signal intensity was measured and quantified on the whole dataset composed of 1272 images. p-values > 0.1) which means the generalization capability of the system among different devices.On the other hand, we evaluated the capability and assessed the robustness and generalization capability of our quantification method between two different smartphone models. To test this, we used only the images obtained by one smartphone model to fit the regression model, and then, the obtained fitting curve was evaluated with the pictures taken with the other model. We did the same process with the other phone model. Moreover, we also performed the experiment using only the images of the same model for both fitting and evaluation. Fungal disease has been neglected for many years. WHO has recently established a priority list of fungal pathogens that will hopefully help to reduce the two million deaths they cause each year, mainly in low- and middle-income countries . Access POCTs are being increasingly incorporated into the diagnostic portfolio for infectious diseases . They arThe use of an AI-app-based specifically designed to read and interpret POCTs implies an automatic, objective, and standardized procedure decreasing subjective interpretation as well as, covering the inherent limitations associated with the visual reading of the test—different workers, with different training and with different visual acuity. These systems provide an objective judgment, as well as help to standardize in the real world the innate sensitivity and specificity of the POCT approved by the regulatory organizations based on data obtained through experiments performed in highly controlled situations. Previous work has proposed the combined use of a mobile app and AI algorithms to digitize and interpret POCT results that have been shown to be usable with a variety of different SARS-CoV-2 POCTs . In addiOn the other hand, smartphones are now a global tool that, among other uses, have shown great capability of data collection and transmission. AI algorithms embedded in mobile phones can be transformative for the diagnosis of diseases especially when high sensitivity and specificity POCTs are available, as is the case of CrAg LFA test. For life-threatening diseases, it is key for the patient to be diagnosed and treated as soon as possible. The use of this approach decreases the need for training healthcare workers offering them both reading systems, visual and automated. Moreover, the digitization of the LFA test allows quick communication with the physicians in charge of the patient, rapid instauration of treatment increasing chances of survival, second opinions as well as storing the results and the patient’s data in a database in the cloud which facilitates, among other things, the estimation of the burden of the disease investigated.In this work, we have described the design, development, and validation of an AI-based mobile application able to automatically read CrAg LFA. The proposed system, which does not require additional hardware and can be installed from regular app marketplaces in any mobile phone, not only is capable of performing a qualitative reading of the POCT  but is able to predict antigen concentration based on the signal intensity of the band on the POCT, providing a quantitative reading. All AI results along with POCT images are sent to a cloud platform that allows for case identification, quality control, and real-time monitoring.Our qualitative reading algorithm shows an area under the ROC curve (AUC) of 0.997 (95% CI: [0.992–1]) when comparing the visual interpretation of CrAg LFAs and AI predictions. Moreover, the algorithm improves the limit of detection compared to the visual interpretation, as it detects weak bands  that are not usually detected by the eye. Having a lower limit of detection will allow us to identify patients that need to be fully diagnosed and treated according to the results obtained which will decrease the mortality rate of this opportunistic infection. For life-threatening diseases such as cryptococcal meningitis, false negative results are of serious consequence. False positive results can be managed accordingly with other parameters related to the specific disease.On the other hand, we have demonstrated the ability to predict CrAg concentration by just relying on a picture of the POCT by measuring signal intensity. We found a strong correlation between signal intensity and antigen concentration, with a Pearson coefficient (r) of 0.953 (95% CI: [0.946–0.959]) but for a limited working range established between 0 and 100 ng/mL because of the postzone effect. The postzone effect, already described with this POCT ,26, impeIn conclusion, we have proven that a qualitative test can be turned into a quantitative metric with a proper AI algorithm and that performance between different smartphone models was similar.Future work includes further assessments of this approach using real biological samples from patients to provide a clinical evaluation, and the use of tests without postzone effect to clinically evaluate the possibility of using qualitative tests together with AI quantification algorithms to predict meningitis, adjust antifungal treatment, and consequently, improve patient survival.This approach has several advantages as it provides an easy-to-use AI-based mobile app for automatic and objective result interpretation of the CrAg LFA, which is able to reduce reading variability among different health care workers, providing an important help in environments where training is limited and the replacement of health care workers is frequent. On the other hand, the mobile app is connected to a web platform, where all results can be safely stored allowing burden estimates or large epidemiological studies eliminating the need for retrospective analysis of lab records, and providing a valid tool for quality control processes.