Weak fluorescence signals, which are important in research and applications, are often masked by the background. Different amplification techniques are actively investigated. Here, a broadband, geometry-independent and flexible feedback scheme based on the random scattering of dielectric nanoparticles allows the amplification of a fluorescence signal by partial trapping of the radiation within the sample volume. Amplification of up to a factor of 40 is experimentally demonstrated in ultrapure water with dispersed TiO Fluorescence is the radiative component of the spontaneous relaxation of an emitter  from an excited state characterized by a spectral distribution that identifies its nature. Stimulated by the absorption of light at a shorter wavelength, it has been extensively studied and applied for over a century and has found countless applications. Its practical use has increased dramatically with the development of sophisticated fluorescence-based techniques and the availability of a wide range of fluorescent probes and markers, benefiting various fields of investigation and monitoring . In chemFluorescence has also made significant contributions to materials science and nanotechnology. Quantum dots, a class of semiconductor nanoparticles with tunable fluorescence properties, have enabled breakthroughs in quantum information processing and biomedical imaging . FluoresBased on the same theoretical foundations of lasers, we consider a new solution to improve the efficiency of fluorescence emission in a less constrained environment. It is based on the physical principle of random lasers and the multiple scattering of light ,23. EarlCombining the concepts of biological  and randIn this study, we demonstrate the possibility of obtaining significant stimulated fluorescence enhancement from a fluorophore commonly used in cell biology, in an aqueous medium and at a biological pH. Working with biological samples requires careful consideration of suitable fluorophores, potential photodissociation, photobleaching or phototoxicity induced by optical pumping and by scatterers added to the sample. Some of these constraints apply also to other fields but are typically not all simultaneously present; their concurrent fulfillment ensures a broader potential for applying the technique. We note that the amplification obtained in the course of this work also leads to a spectral narrowing of the fluorescence, thus adding to the detection of intrinsically weak fluorescence signals the advantage of denser multiplexing of fluorochromes for  parallel identification . After dThe aim of this experimental work is to present a flexible amplification technique that can be applied in different fields. Therefore, instead of choosing the conditions that may give the best results but are not necessarily widely applicable, we choose average conditions that allow a better assessment of the potential usefulness of our proposal. The medium in which we test amplification is water, so to obtain good amplification, the refractive index of the NanoParticles (NPs) must be compared with that of this medium. Changing the medium will require rescaling.We choose Fluorescein-5-Isothiocyanate (FITC), a broadly used fluorophore in biological applications—traditional and innovative —with gooTitanium dioxide nanoparticles  compare@ 500 nm ). The hi [n≈1.33 ,41, i.e.strength  within t process ,42,43.As one of the mechanisms to obtain amplification relies on achieving the stimulated emission regime, FITC pumping is performed with a pulsed laser, as is common in the literature . The higConsidering pump pulses with energy in the range of νp=10 Hz , the expTo a solution of FITC  in ultr TX, USA ), at conHaving chosen a good but not optimal fluorophore, we analyse the performance of its dilutions to obtain low self-quenching  at moderF>200 μM a, the flL is the sample thickness  ,42, and The mean diameter of TiOfication ) when sumplitude ; (ii) lomplitude . The latThe physico-chemical equilibrium of NPs is ensured by the mutual repulsion ,48, quanty limit  and showA quantitative measure of the clustering in the suspension is obtained by measuring the hydrodynamic radius of the NPs, ng (DLS) ,53,54  allows individual pulse monitoring on P1 a. The puThe beam transmitted by S, with pulse energy in the range 100 The backscattered fluorescence pulses emitted in response to each excitation are collected by L1 (estimated NA = 0.17), spectrally filtered by the dichroic element, DM, to remove residual energy at the pump wavelength, attenuated (if necessary) by the set of ND filters F2 (Kodak Wratten II) and focused on the detector by a second lens L2. The fluorescence is detected either by a fast photomultiplier detector .The acquisition system is designed with the following features:The first point is necessary for post-treatment in cases where pulse-to-pulse variability may mix nominally different pulse energies, thus allowing meaningful comparison of the observed fluorescence. The second point arises from the presence of photobleaching  and the For quantitative measurements, careful control of the number of pulses and their synchronized detection are required. The mechanical shutter at the output of the laser not only prevents photobleaching of the FITC, but also ensures the synchronization of all operations b, particThe prepared homogeneous solutions of FITC and TiOleaching  .4.For each energy and sample, we compute the mean 5.M is the number of repetitions  :(3)Y¯=1The analysis of the amplification signals was carried out according to the following procedure:The addition of increasing concentrations of TiO spectra a at the nergy EP b shows ainset of b. The suAccompanying the enhancement, a spectral narrowing of the collected fluorescence is observed as illustrated by the shape of the normalized spectra a for theThe pump pulse has a duration  τf≈4 ns . Thus, tIn the non-stimulated emission regime, the fluorescence pulse duration sources  and is collected in the solid angle corresponding to the numerical aperture of the optics . The contrasting behavior reflects the conceptually different nature of the quantities being plotted: while the fluorescence intensity It is interesting to note that the overall shape of the gain curves b is diffThis is good news for many applications  since half of the total gain can be obtained at less than 1/3 of the maximum pump pulse energy, in the range we have explored. Two different strategies are therefore possible, depending on the scope of the application. In order to maximize the amount of collected fluorescence light, it will be worthwhile to increase the pump pulse energy, whereas to obtain the greatest benefits in terms of gain efficiency . However, if lower scattering densities are preferred, it is still possible to obtain ℓ), which represents a substantial gain from an experimental point of view since an increase of one order of magnitude clearly raises a weak signal well above the background noise.Finally, it is important to note that the absolute amount of gain obtained with this setup is considerable. Additional evidence for the role played by the scatterers is provided by the photobleaching curves.  density  give eveThe results of this investigation show that by adding TiOcent dye ) with a cent dye .The stimulated amplification is evidenced by the observation of an increased fluorescence yield, a significant reduction in linewidth (up to four or five times) and a shorter fluorescence pulse duration. In applications, the optical linewidth reduction can be used to provide improved detection when different fluorophores are used simultaneously to label different agents. Optical amplification is achieved at sufficiently low pulse energies, limiting photodissociation, photobleaching or phototoxic effects. Other types of NPs can be considered , depending on the experimental conditions .The strong amplification of a fluorescent signal paves the way for numerous applications in biology, environmental sensing, chemical detection, food safety, to name but a few. The greatly increased signal strength allows the detection thresholds to be lowered, enabling contamination, pollutants or generally low populations to be easily identified using the same detection chain. Wavelength multiplexing is facilitated by the significant narrowing of the fluorescence line, as the spectral signatures of the different fluorophores become more easily identifiable. In addition, crosstalk between the short-wavelength emission tail and the long-wavelength reabsorption tail—i.e., self-quenching—is greatly reduced. Finally, the nanosecond timescales of pulsed fluorescence can be exploited for time-resolved monitoring.


High-aspect-ratio carbon nanotubes can be directly mixed into polymers to create piezoresistive polymers. Reducing the cross-sensitivity and creating unidirectional sensitive sensors can be achieved by aligning the nanotubes before they are cured in the polymer layer. This research presents and characterises this alignment of carbon nanotubes inside polydimethylsiloxane and gives the corresponding strain sensor results. The influence on the alignment method, as well as the field strength, frequency and time is shown. An analytical model is created to investigate the sensor’s behaviour and determine the effect of electron-tunnelling in the sensor. A numerical model gives insight into the necessary applied field strength, frequency and time to facilitate alignment in viscous liquids. The experimental data show a two-phase piezoresistive response; first, a linear strain response, after which the more dominant electron-tunnelling piezoresistive phase starts with high gauge factors up to k ≈ 4500 in the preferential direction, depending on the carbon nanotube concentration. Gauge factors in the orthogonal direction remain low (k ≈ 22). Finally, the dynamic stability of the sensors is proven by exposing the sensors to a cyclic strain. Small initial drifts are observed but appear to stabilise after several cycles. Carbon nanotubes (CNTs) have emerged as a versatile and promising material for enhancing the properties of polymers in various applications, particularly in the field of piezoresistive sensors. The integration of high-aspect-ratio CNTs into polymer matrices has started a whole new field of piezoresistive polymers capable of accurately sensing mechanical deformations and strains. These sensors are applied in a very wide range of fields, including aerospace ,2,3, strThe orientation of the CNTs within their host material can be altered by applying an external electric field. The possible advantages of aligned CNTs can already be intuitively visualised to create connections of high-aspect-ratio CNTs over long, predefined directions. Thermal or electrical conduction paths can be created in a preferred direction, where in all other directions, the conductivity is decreased. These selective conductive paths can be utilised for directional strain sensing with very high gauge factors. Regular carbon nanotube-based sensors often feature relatively low gauge factors (in the order of 0.5–4) ,15,16,17Even higher sensitivities for very small strain regions (up to 0.10%) are found in the literature that are based on piezotronic tunnelling junctions and shown to have a gauge factor up to 4.8×105 .This study aims to investigate, characterise and optimise the alignment of carbon nanotubes within polydimethylsiloxane and assesses its effects on the performance of piezoresistive sensors. This alignment of carbon nanotubes in a specified direction minimises the cross-sensitivity of the sensor. An ideal sensor features no electrical connections in all other directions and only reacts to the direction of the applied strain. The experimental data are supported by extensive numerical and analytical models, yielding key insights into the working principle of the carbon nanotube alignment due to an applied electric field and the possible high sensitivities due to formed electron-tunnelling connections.Polydimethylsiloxane (PDMS) Slygard 184 was chosen as a suitable polymer to form the basis of the piezoresistive sensing layer. The main reason for this choice was the fact that the elastomer has no additional solvent that needs to evaporate whilst curing the final layer. It was expected that this removal of solvent would have negatively influenced the alignment quality. Additionally, the molecular structures of elastomers (like PDMS) are comprised of very loose, wide and long polymer chains, causing their flexibility properties. PDMS was chosen as the ideal polymer as no additional solvents were needed and it is well known in the literature and IC technology industry.The sensor fabrication was completely performed inside a clean room with a regulated temperature and humidity. The characterisation of the sensors was performed in a climate-controlled laboratory. It is known that humidity changes the resistivity of carbon nanotube–polymer layers ,23. To fThe manufacturing process needed two sets of electrodes: alignment electrodes and measurement electrodes. The first were sputtered directly onto a 4-inch glass wafer and isolated by a 5 ous work . The golThe sensor was based on the fact that when applying a tensile strain, the distance between the conductive particles increases and the conductivity decreases. Ideally, with the aligned CNTs, the sensitivity is increased in the preferred direction and reduced to zero in all others. The individual sensors were placed in a custom-made gripper with copper plates to continuously measure their resistance (shown previously in ). The whThe experimental data were supported by both numerical and analytical models. The first model was focused on the principle of rotating individual carbon nanotubes in a liquid medium and the associated electric field strengths, frequencies and viscosity of the liquid. The analytical model detailed the possible sensor piezoresistive responses due to electron tunnelling and loss of conductive networks.The alignment principle is based on the fact that the mere presence of dispersed nanotubes in a medium exposed by an electric field causes field inhomogeneities. The major force behind the CNT-CNT connections is due to the Coulombic attraction between oppositely charged ends of carbon nanotubes ,26. Due In the presence of an electric field, the conductive carbon nanotubes are polarised and experience a dipole moment. The induced torque acts on the carbon nanotube and aligns it with the electric field ,29. Thiss.A loss of conductive networks due to the reorientation of CNTs within the polymer matrix. The CNTs change their orientation and position due to the applied strain. In general, it is assumed that the CNT-CNT connections start breaking up with increasing strain. As the polymer matrix is highly flexible, the effects are reversible with a decreasing strain. This relation is shown by Equation , where tElectron tunnelling when the CNT-CNT distance is closer than 1.0 nm. The carbon nanotubes within this distance can conduct current, which with the increasing strain will abruptly stop when the distance becomes too great.Two main principles of piezoresistivity are expected to occur while the sensors are experiencing tensile strain:The more interesting effect due to the alignment of CNTs is the electron-tunnelling effect, which could theoretically increase the gauge factor by multiple orders of magnitude. The electric field causes the CNTs to rotate and align in the direction of the induced field. If the CNTs come close together (<1.0 nm), a current can flow between the CNT-isolation-CNT barrier. This tunnelling effect depends on the distance between the media and its barrier height. The tunnel resistance is shown in Equation , based oA (OD = 50 nm), tunnelling current density J, Plank’s constant h, tunnelling distance d, mass of the electron m and the barrier height The cross-sectional area of the CNT is denoted by or epoxy . The CNTor epoxy , PDMS: 0or epoxy ) and weaor epoxy . Hence, x and y directions were included to ensure a slight random positioning. A valid electrical connection was determined when either the nanotubes were in direct contact or close enough for tunnelling (<2.5 nm in this model). The conductive paths were determined  and the resistance was calculated for each connection. This was done either via determining the resistance of the connecting “wires” . Two main electrodes at the top and bottom and a specified number of random or aligned rectangles.Determination of the closest distances between all rectangles. The rectangle borders are implemented for this, not the centre points.The shortest path is determined between the electrodes via Dijkstra’s shortest path algorithm.A strain on the sensors is simulated by changing the y-coordinates of all objects, just as with a real applied strain.The distances and shortest paths are determined once again for all applied strains.The resistance of each connection is determined, either via tunnelling or direct contact. Electron tunnelling is possible for distances lower than 2.5 nm, featuring the exponential relation between resistance and distance. The direct contact resistance is determined by the length and width of the connection.Finally, multiple parallel conductive connections are modelled and their parallel resistance is determined.It is expected that after the alignment of carbon nanotubes in the polymer is complete, conductive paths have been formed. Initially, this would mean the nanotubes are in contact before the applied strain. The nanotubes are slowly pulled apart until the first connections break and electron tunnelling occurs and suddenly jumps the linear strain response to an exponential growth. This property is also seen in the analytical simulations and shown in x-axis).Ideally, if all vertically conductive paths are perfectly aligned, a strain in the orthogonal direction  should have no effect on the sensor. However, due to possible cross-connections, a small change is still expected. The results of the strain sensitivity in the direction orthogonal to the alignment direction is shown in The loss of connections is shown in x- and y-direction. The applied electric field is in the y-direction and the CNT has a starting angle of 30x-axis. With alignment, the x-component of the load decreases, as the y-component increases. Eventually, the nanotube stabilises in the aligned direction. Furthermore, as depicted in The concept of rotating CNTs inside a liquid medium using an external electric field was validated through a COMSOL Multiphysics model. The model consisted of a single CNT  resulted in a longer alignment time. Conversely, an increase in electric field strength decreased the alignment time. These observations suggest that a higher viscosity requires more time for the CNTs to align with the applied field, while stronger electric fields expedite the alignment process.This information provides insights into how viscosity and electric field strength can influence the alignment kinetics of CNTs in a liquid medium. Additionally, the first values of the needed field strengths and frequencies for the experiments are now known.If carbon nanotubes attach to the conductive electrodes, they can create local areas of increased electric field strengths and cause alignment imperfections. This effect is simulated and demonstrated in Carbon nanotubes were mixed in deionised water and aligned with two electrodes on either side in a 3D-printed mould (1 cm spacing). The results are shown in Using a DC voltage yielded the same alignment effect but with the major disadvantage of slowly pulling all charged CNTs to a single side. This was experimentally proven by applying a DC voltage of 13.3 kV/m and measuring the current during alignment. It is expected that the migration of nanotubes when positioned in a DC electric field is caused by the initial charge of the nanotubes. Depending on the manufacturing process of the carbon nanotubes, they can become charged. For example, if the CNTs are treated with acidic functional groups, they can become positively charged. Basic groups can cause negatively charged CNTs . This haThe CNT concentration was lowered even more to try and visualise the effect of the alignment on the conductivity of the solution. Two different frequencies were applied and the results are depicted in After the initial experiments, the alignment parameter characterisation was performed with a manufactured mould featuring an electrode distance of 3 mm and a length of 1.5 cm. Two alignment methods were characterised: with the direct current application (electrodes inside the liquid) or an indirect alignment where the electrodes were isolated from the liquid. The alignment process was investigated for the following parameters: electric field strength, alignment time, indirect vs. direct alignment and frequency influence.For the piezoresistive layer, PDMS with a 1:5 curing agent ratio was chosen. Normally, the standard ratio for the curing agent is 1:10. However, in this case, the proportion of the curing agent was increased to the maximum value that still yielded proper layers, which was a ratio of one to five. This adjustment was made to create the least viscous solution possible, which is beneficial for the alignment process.The necessary electric field strength required to induce optical alignment of CNTs was investigated. A fixed frequency of 1 Hz was used for this study. If, after 60 min, no optical change in CNT alignment was observed, it was assumed that the applied field strength was not sufficient. Results showed a very precise window of field strength needed for aligning the CNTs in PDMS. An induced electric field of 460 kV/m did not result in an optical change in the CNT orientation, while with 500 kV/m, alignment occurred almost instantly.As suspected, the speed of alignment increased with higher field strengths. To achieve better control in the alignment process, a field strength of 480 kV/m was chosen. This specific field strength produced an optical change in the CNT alignment after several minutes, which was deemed feasible for later wafer fabrication and sensor production.The CNT-polymer samples were subjected to an indirect electric field of 480 kV/m at 1 Hz for up to 60 min. Microscopic images were taken at intervals of 5 min, capturing the starting position, alignment after 5 min and alignment after 60 min, as shown in Furthermore, it was found that as the CNT weight percentage (wt%) in the polymer increased, the alignment of CNTs took longer. Beyond a certain CNT concentration, no more visible optical alignment was observed due the large clusters in the mixture.As mentioned before, two alignment methods are possible. Either the electrodes are placed in the solution, enabling a current to flow between the electrodes once conductive paths are formed, or electrodes are isolated. Both methods were investigated, and the results were clear. The indirect method was able to align the CNTs in the same  way as the direct method. However, difficulties arose with the direct method, specifically with the sudden connection between both electrodes and the high required voltages. Additionally, with the direct alignment method, it was observed that after the solution was optically aligned, the edges on either side started moving turbulently. A circular motion was visible on either side, while no movement was visible in the middle. It is theorised that this effect is caused by the change in the local electric field orientation due to the CNTs attached to the electrodes, as previously discussed and shown in Due to these results and the challenges encountered with the direct method, the indirect method was chosen for aligning the CNTs in the wafer-fabricated sensors. The indirect method demonstrated a successful carbon nanotube alignment without the associated complications.Frequencies of 1 Hz, 10 Hz, 100 Hz and 1 kHz were investigated with a fixed voltage of 480 kV/m for up to 60 min. The time it took to optically move and align the CNTs was taken as a comparative study between the frequencies. Results are shown in Sensors were fabricated with four different CNT concentrations  to investigate their influence on sensor quality. Typically, concentrations below 0.2 wt% were considered to be nonconductive. Therefore, any measured conductivity change was attributed to the alignment process.The glass wafers  were placed on the spin-coater and a 65 Depending on the added CNT concentration, the layers were optically transparent (<0.2 wt%), or almost black-coloured (0.33 wt%), as shown in The alignment was inspected via an optical-light microscope. The results immediately before and after alignment are shown in The unidirectional behaviour of the sensor was investigated by creating two different IDE-design structures on top of the sensing layer. The sensor is based on the fact that with applying strain, the distance between the conductive particles increases and the conductivity decreases. Ideally, with the aligned CNTs, the sensitivity is increased in the preferred direction and remains unchanged in all others. This is explained more clearly in The base resistance of all samples was measured and is plotted in The carbon nanotube-aligned piezoresistive strain sensors exhibited, similar to the analytical simulations, a two-phase response. For the first small strain range, the electron-tunnelling effect appeared not to be the dominant factor and was combined with the regular piezoresistive effect. It is theorised that a large part of the CNT-CNT connections stay connected and only shift, resulting in linear resistance changes. After a certain threshold was reached, electron tunnelling occurred due to the increased change in disconnecting CNT-CNTs, drastically increasing the response of the sensors up until a point where no more conductive paths were present.Results of all sensors clearly indicated a great sensitivity change within the measured strain regions (up to 0.7%). Results with an interdigital electrode distance of 200 Additionally, the effect of the interdigital electrode spacing is shown in It was found that the concentration of carbon nanotubes does not play a major role in the maximum achievable resistance change. All nanotube concentration sensors saturated around a resistance change of 1600%. This is mainly caused by the fact that all aligned sensors featured a starting resistance on the same order of magnitude, and the upper limit was set by the maximum measurable resistance of the high-precision multimeter . The interdigital electrodes featuring a parallel orientation to the alignment direction were found to have a gauge factor of around ≈22. The sensors featured a two-phase piezoresistive response. Initially, the sensors showed a linear response region, after which the electron-tunnelling effect became more dominant, resulting in a high gauge factor response. This is summarised in The base resistance of the aligned sensors also showed a clear distinction in conductivity between the parallel and perpendicular IDE structures, indicating a change in the CNT-orientation network.The behaviour of the rotating carbon nanotubes and the expected piezoresistive effect was analytically and numerically modelled and confirmed later by experimental results. The analytical model showed high gauge factors reaching up to 4000 for aspect ratios of 100–250, corresponding to the experimental values. The analytical model showed an inverse relation between the number of nanotube connections and sensitivity, which was proven to be identical for the fabricated sensors in this research. The numerical simulation showed the order of magnitude necessary for the rotation of carbon nanotubes due to the presence of an electric field. The reasoning for the effect of the turbulent alignment with the direct current alignment method was also shown in the numerical model and experimental results.The alignment of carbon nanotubes is greatly influenced by the field strength, frequency and time. An alternating field stops the nanotubes from migrating toward an electrode, and a longer time creates thicker agglomerated nanotube bundles. However, due to the cross-connections between the conductive pathways, an absolutely unidirectional sensitive sensor is not possible yet. Future research will investigate the possibility to align functionalised carbon nanotubes to enhance the alignment and improve the unidirectional sensor properties. The functional groups in the nanotubes cause a repulsive interaction between the aligning CNTs, increasing the alignment quality and minimising the cross-sensitivity. Another advantage is the fact that the functional groups increase the charge in the carbon nanotubes, increasing their dipole moment .Additionally, first results showed an increase in the sensors’ sensitive region by decreasing the interdigital electrode distances. Future research could utilise this property to create CNT-aligned sensors with far greater (linear) sensitive regions.


The near-isothermal rolling process has the characteristics of multi-variable and strong coupling, and the industrial conditions change constantly during the actual rolling process. It is difficult to consider the influence of various factors in industrial sites using theoretical derivation, and the compensation coefficient is difficult to accurately determine. The neural network model compensates for the difficulty in determining the compensation coefficient of the theoretical model. The neural network can be trained in advance through historical data, the trained network can be applied to industrial sites for prediction, and previous training errors can be compensated for through online learning using real-time data collected on site. But it requires a large amount of effective historical data, so this research uses a combination of production data from a controllable two-roll rolling mill and finite element simulation to provide training data support for the neural network. Five trained neural networks are used for prediction, and the results are compared with industrial site data, verifying the reliability and accuracy of genetic algorithm optimized neural network prediction. We successfully solved the problem of low control accuracy of TiAl alloy outlet thickness during near-isothermal rolling process. Its properties include low density 3.9–4.2 g/cm g/cm3, hIntelligent factories have steadily gained popularity ,5 in recNeural networks have been extensively employed in the past several decades to anticipate rolling parameters. Rolling force plays an important role in the rolling process, and the accurate prediction of rolling force is extremely important for the forming performance of sheet metal. In order to increase the accuracy of the rolling force forecast using a neural network model, Zhou et al.  continueA large amount of research has also been conducted on the optimization of BP neural networks. Chen GY et al.  establisThe use of genetic algorithm (GA) for optimizing neural networks has also made good progress. A Neural Network Model Optimized by GA is a new prediction model for predicting the rolling parameters. Domestic and foreign scholars have carried out many studies to evaluate its performance in the prediction of different parameters, such as determining the metallurgical transformation of steel ,28, predThere is no research on the prediction of exit thickness of near-isothermal rolled TiAl alloy, despite the fact that an artificial neural network (ANN) is frequently employed in the prediction of the rolling process. Compared with finite element methods, neural networks require a large amount of data for learning. Therefore, in order to train high-quality neural networks, finite element models are used to expand the training dataset, ensuring the neural network has good generalization ability . The avaIn the hot rolling process, the rolling force of the roller on the TiAl alloy causes plastic deformation to achieve the desired target thickness. On the other hand, the TiAl alloy will also provide a reversing force to the roll, causing it to flatten elastically. This will vary the spacing between the rolls, which will modify the thickness of the finished product. The bounce equation of the rolling mill is the theoretical basis for predicting the exit thickness:The stiffness model can be expressed as follows:Work roll wear and backup roll wear are the two main categories of mill wear. By differentiating the work roll over its length, it is possible to obtain the work roll wear model at unit speed:Similarly, the wear model of the backup roll can be expressed as follows:Therefore, the mill wear compensation value at unit speed should be:y-coordinate direction:The temperature of the work roll is primarily impacted by heat conduction from the TiAl alloy and cooling water during the actual production process. For the analysis, a simple model is typically employed. The following equations represent the thermal expansion of the roll in the axial The effectiveness of the finite element model established in this study was verified by comparing the exit thickness obtained from the finite element model with the experimental data. The rolled plate size is 100 From Although the BP neural network model is considered an excellent prediction model with high fault tolerance and adaptability, it also has some evident drawbacks, such as sluggish convergence speed and an easy tendency to slip into the local minimum. Different strategies are suggested to optimize the BP neural network  in orderThe study of computer simulations of biological systems gave rise to the genetic algorithm (GA). With inspiration from both Gregor Mendel’s theory of genetics and Charles Darwin’s theory of evolution, it is a stochastic global search and optimization technique designed to replicate natural evolutionary processes. It is essentially a fast, parallel, and global search strategy that can automatically gather knowledge about the search domain, adaptively controlling the search process to obtain the best answer. It is advised that readers consult the detailed principles of genetic algorithms .By using global optimization and the implicit parallelism of genetic algorithms, the optimization speed of weight coefficients can be improved. The basic process of network optimization is shown in A neural network’s ability to anticipate outcomes is directly determined by the relationship between its input parameters and the thickness of the rolling exit. The forecast result will differ from the real thickness if too few factors are used, and the prediction capability will be lost. The learning and training of the network will be slowed down by too many parameters, and the accuracy of the predictions will not be increased or even lowered. Therefore, choosing the right input parameters is crucial for the effectiveness of network prediction.As indicated in The correlation analysis of the reduction ratio is conducted using the GRA approach, which has been utilized extensively in recent years to choose data features for prediction models ,48. The The mill stiffness and reduction ratio have a direct impact on the final thickness of TiAl alloy, while the rolling speed has an impact on the thickness through affecting the deformation resistance, oil film thickness, and friction coefficient. The inlet temperature alters the thickness of the material by modifying its resistance to deformation and altering the rolling force necessary for plastic deformation.The input layer, hidden layer, and output layer make up the neural network. The number of hidden layer units directly affects the ability of neural networks to predict the thickness of the rolled TiAl alloys, as, once the input parameters are established, the number of units in the input and output layers can be determined. A process of trial and error is used in this study to assess the hidden layer unit count from 1 to 10. The root mean square error (RMSE) results predicted by the five algorithms are shown in The near-isothermal rolling exit thickness of the TiAl alloy is accurately predicted using the GANN model, and the rolling parameters are tuned to prevent cracking. The rolling effect is depicted in (1)After comparison, the GANN model has high prediction accuracy, with a maximum prediction error of only 0.18 mm, an average prediction error of 0.05 mm, and a root mean square error of 0.0064;(2)The GANN model has the function of online monitoring, with a training time of 1.8457 ± 1.2359 s and a testing time of 0.01284 ± 0.01157 s;(3)As the rolling speed increases, the entrance temperature increases, the stiffness coefficient increases, and the outlet thickness decreases;(4)Neural networks have the characteristic of fast response, and using this powerful tool to create more intelligent devices for human society will have a significant impact on the future.This article predicts the outlet thickness of near-isothermal rolled TiAl alloy using five neural networks, and after comparison, the following conclusions are drawn:


Piezoceramic transducers (PCTs) bonded to carbon fiber-reinforced plastic (CFRP) composite structures must be durable as well as remain properly bonded to the structure in order to provide reliable data for accurate guided-wave-based structural health monitoring (SHM) of aeronautical components. The current method of bonding transducers to composite structures through epoxy adhesives faces some shortcomings, such as difficult reparability, lack of weldability, longer curing cycles, and shorter shelf life. To overcome these shortcomings, a new efficient procedure for bonding the transducers to thermoplastic (TP) composite structures was developed by utilizing TP adhesive films. Application-suitable TP films (TPFs) were identified and characterized through standard differential scanning calorimetry (DSC) and single lap shear (SLS) tests to study their melting behavior and bonding strength, respectively. Special PCTs called acousto-ultrasonic composite transducers (AUCTs) were bonded to high-performance TP composites (carbon fiber Poly-Ether-Ether-Ketone) coupons with a reference adhesive (Loctite EA 9695) and the selected TPFs. The integrity and durability of the bonded AUCTs in aeronautical operational environmental conditions (AOEC) were assessed in accordance to the standard Radio Technical Commission for Aeronautics DO-160. The AOEC tests performed were operating low and high temperatures, thermal cycling, hot-wet, and fluid susceptibility tests. The health and bonding quality of the AUCTs were evaluated by the electro-mechanical impedance (EMI) spectroscopy method and ultrasonic inspections. The AUCT defects were created artificially and their influence on the susceptance spectra (SS) was measured to compare them with the AOEC-tested AUCTs. The results show that a small change occurred in the SS characteristics of the bonded AUCTs in all of the adhesive cases after the AOEC tests. After comparing the changes in SS characteristics of simulated defects with that of the AOEC-tested AUCTs, the change is relatively smaller and therefore it can be concluded that no serious degradation of the AUCT or the adhesive layer has occurred. It was observed that the most critical tests among the AOEC tests are the fluid susceptibility tests, which can cause the biggest change in the SS characteristics. Comparing the performance of the AUCTs bonded with the reference adhesive and the selected TPFs in the AOEC tests, it was seen that some of the TPFs, e.g., Pontacol 22.100 outperforms the reference adhesive, while the other TPFs have similar performance to that of the reference adhesive. Therefore, in conclusion, the AUCTs bonded with the selected TPFs can withstand the operational and environmental conditions of an aircraft structure, and hence, the proposed procedure is easily installed, reparable, and a more reliable method of bonding sensors to aircraft structures. Carbon fiber-reinforced plastic (CFRP) composite materials are high-performance materials that are increasingly used as a primary material for engineering structures in the aerospace, wind energy, naval, and other industries. Due to their extraordinarily high mechanical performance, reduced weight, and high durability, as compared to traditional materials such as aluminum or steel, there is growing use of these materials in structural applications . These aComposite structures are vulnerable to impact damage during operation, especially barely visible impact damages. They may exhibit a variety of structural failure cases, such as delamination, fiber breakage, and matrix cracking, among others . The mecStructural Health Monitoring (SHM) offers a paradigm shift from a schedule-driven maintenance to a condition-based maintenance approach. It provides a rational approach by enabling cost-effective risk-based maintenance schedules based on predictions of the remaining useful life as opposed to periodic inspections. SHM is defined as a process of collecting and analyzing data from a distributed network of sensors that are mounted on or embedded inside a structure to obtain information about the health of the structure . In receSHM using piezoceramic transducers (PCTs) has relatively higher maturity and is being widely used for SHM of composite structures . It is oOne of the challenges in the upscaling of guided-wave-based SHM in aerospace structures is the fast and cost-efficient integration of PCTs to composite structures. Generally, two methods are used to integrate the PCTs with the structures, namely co-bonding and secondary bonding ,9,10. InDuring operation of an aircraft, both the PCT material as well as the adhesive layer of the bonded PCTs are prone to damage and degradation . As poinTM ::Yfree(ω)b, l, and t are the width, length, and thickness of the PCT, respectively; The admittance of a bonded PCT known as electro-mechanical admittance (EMA) is given in Equation  as:(2)Y or EMA spectra can evaluate the health as well as bonding condition of a PCT and has been used by many studies as an criterion to evaluate the sensor health and debonding ,15,34,35n is the number of points, and The changes in the above performance indices are calculated from the percentage root mean square deviations (RMSDs) calculated after each AOEC test and is defined in Equation  as: (3)RTo understand how different AUCT faults affect the susceptance spectra (SS), the defects that can occur on a AUCT during its lifetime were created artificially and their influence on the SS was measured. The measurements were used as a reference in order to compare the post-test SS of the AUCTs under test with that of the faulty AUCTs in order to determine if any defect or degradation had occurred on the AUCTs or the adhesive layer during the AOEC tests. The AUCTs were bonded to CF-PEEK composite coupons with the reference adhesive and three kinds of commonly occurring AUCT defects were created, namely wear-off, breakage, and debonding. The wear-off was created in three grades. In the first grade, some part of the encapsulation of the AUCT was removed such that the piezoceramic was not visible, in the second grade, the encapsulation layer was completely removed such that the piezoceramic became visible, and in the third grade, severe wear-off was carried out by removing the piezoceramic material as well. The debondings were also introduced in three levels, namely 25%, 50%, and 75% of the AUCT was debonded. In case of the AUCT breakage case, only 15% of the piezoceramic was broken and rest was kept healthy and well bonded.Ultrasonic (US) inspections were performed to further inspect the AOEC-tested AUCTs bonded with different adhesives under consideration. The inspections were carried out with an immersion tank Triton 8000TT+ from TecniTestNDT. The Pulse-echo method was used with a scanning speed of 50 mm/s and scanning index of 1 mm to generate the C-scans registers as well as A-scan for each point of register. The AUCTs were sealed with blue tape so that no water went inside the adhesive layer. Reference scans were taken for the AUCT’s with artificially introduced debonding of 25%, 50%, and 75%, so that they can be compared with the US scans of the AOEC-tested AUCTs and determine if any significant debonding has occurred in the adhesive layer.Differential scanning calorimetry (DSC) tests were carried out to study the melting behavior and crystallinity characteristics of all thirteen identified TPFs. Although the melting point  tests were carried out to evaluate the bonding quality of the TPFs on PEEK surface and compare them with the reference adhesive. Only those TPFs were tested that had the desired melting behavior as obtained from the DSC tests and that had passed the reparability tests. In total, eight films were tested, including the reference adhesive. The tests were carried out on a MTS universal testing machine according to the standard EN 2243-1 by bonding CF-PEEK (HTA-40) composite specimen to each other with the selected films. At least three specimen were prepared for each case.The AOEC tests were carried out according to the standard DO-160. The following tests were carried out: low and high temperature, thermal cycling a, hot-weThe DSC tests were carried out on all the thirteen selected films that met the required criteria. The The TPF7 supplied by L&L products did not show any clear All the TPFs which did not have the desired melting behavior were not tested for reparability and bonding strength, except for TPF7 and TPF8. An exception was made for the TPF7 because of the high adhesion properties mentioned by the supplier were to be verified during the SLS tests. TPF8 was also tested because the two melting regions were inside the range of the set criteria. Therefore, the TPFs TPF4 and TPF9 to TPF13 were rejected and not used further in the study.Guided waves generated by an AUCT bonded by the reference adhesive and received on AUCTs bonded with the reference adhesive, TPF1 and TPF7 at 250 kHz in a pitch-catch configuration are shown in In The SLS tests were carried out for the reference adhesive and all the TPFs which passed the reparability tests, i.e., TPF1–TPF3 and TPF5–TPF8. The objective was to evaluate and compare the bonding quality of the TPFs with that of the reference adhesive. The SLS test load-displacement curves for the reference adhesive and the TPFs are shown in The SLS strength of most of the TPFs is comparable to that of the reference adhesive except in case of TPF3 and TPF8. One of the adhesive films that stood out was TPF7; it was found that the SLS strength of this film was even higher than the reference adhesive, and hence, it can be concluded that it has really good adhesion properties as specified by the supplier and a good candidate to bond the AUCTs. The TPFs  have acceptable SLS strength, whereas TPF3 and TPF8 have very low SLS strength. The reference adhesive which is an epoxy material and TPF7 both have a hard and brittle behavior, which is typically shown by thermoset polymers. This shows that TPF7 behaves more like a thermoset material but is reprocessable as well. The remaining TPFs shows a more ductile behavior as an elongation region can be observed before the break.As mentioned, three commonly occurring AUCT defects were artificially created and their influence on SS was measured. The influence of these three defects, namely wear-off, AUCT breaking, and debonding, on the SS as compared to the baseline  measurements, is shown in The AUCT wear-off causes a decrease in the slope of the SS. The percentage RMSD in slope between the healthy and three wear-off levels are 0.5%, 4%, and 38.6%, respectively. This means with severe AUCT degradation, there is a significant change in the SS slope. After each wear-off level, the amplitude of the first resonant peak decreases more, while the resonant frequency shifts towards the lower values. The deviation in the resonance amplitude and shift in the resonant frequency at severe wear-off is 34.1% and 7.2%, respectively. After severe wear-off, only the first resonant is clearly visible. This can be explained by the fact that the wear-off removes some of the piezoelectric material, and therefore, the admittance is the ability of AUCT to pass the current decreases significantly. The debonding produces a similar influence on the SS as that of the wear-off, i.e., the decrease in the SS slope, decrease in the first resonance amplitude, and shift of the resonant frequency towards the lower values as the amount of debonding increases. The percentage RMSD between the healthy and 25%, 50%, and 75% debonded AUCTs for slope, resonant amplitude, and resonant frequency are 2.9%, 12.5%, and 9.4%; 16.5%, 25.0%, and 30.4%; and 2.3%, 10.9%, and 14.9%, respectively. In case of the AUCT breakage, there is a significant change in the slope (30.5%) and the resonant peaks are not recognizable. This is explained by the fact that less piezoceramic material is now contributing to the voltage produced.It can be seen that the defects can have a significant influence on the SS of the AUCTs. The SS curve characteristics that are affected significantly by the sensor defects are the slope, the magnitude of the first resonant peak, and the resonant frequency. Therefore, any significant change in these characteristics can indicate some damage or degradation on the AUCTs or the bonding layer.The bonded as well as free (not bonded) AUCTs were exposed to the AOEC tests, as described in The SS plots of bonded and free AUCTs after each AOEC test are shown from The other two parameters that can give more insights about the specific changes that have occurred in the SS during the tests are the changes in the resonance characteristics, i.e., the amplitude and the frequency of the resonance. From Another interesting thing that was observed during the AOEC tests was that most of the changes that occurred in the SS plots in all the bonded AUCTs occurred during the fluid susceptibility tests. This can be clearly seen in the SS plots for all the bonded AUCTs with different adhesive films. A noticeable change in the SS plots can be observed with the general trend of resonant frequency shifting to the left, as observed in case of artificially created defects and as also reported in ,35. ThisThe results from the US inspections that were carried to further inspect the AOEC-tested AUCTs are shown in A new efficient method of integrating PCTs to TP composite structures was proposed by using TPFs rather than epoxy adhesives. The TPFs were chosen based on certain criteria and characterized with standard tests. The bonding ability of the chosen TPFs was checked by EMI and lamb-wave measurements. The reparability, which is one of the main advantages of TP adhesives, was demonstrated through a very simple setup. To demonstrate the durability of the proposed bonding method in aeronautical applications, the AUCTs were bonded to TP coupons through the chosen TPFs and put through standard AOEC tests. It was shown that the changes produced in the AUCT characteristics during the AOEC tests were significantly smaller than the changes caused due to AUCT defects. Thus, no significant degradation occurred in the AUCT during the AOEC tests. The most critical AOEC tests for all the adhesive films whether the epoxy reference film or the chosen TPFs were the fluid susceptibility tests of Kerosene and Acetone, which introduced the maximum changes in the SS characteristics. However, such scenarios of AUCTs getting immersed in fluids such as Kerosene and Acetone are less likely to occur in real-life applications. Nevertheless, any changes that can occur in the AUCT characteristics because of these conditions should be taken into account in the SHM system. Taking these changes into account can also help the SHM designer to set a threshold to distinguish between the changes in the guided wave signal because of the sensor and structure in order to avoid any false alarms.After comparing the performance of the bonded AUCTs in the AOEC tests, it was seen that some TPFs outperformed the reference epoxy film, while other TPFs had a similar performance, like that of the reference epoxy film. Thus, the proposed method of bonding the AUCTs is more efficient, easy, and reliable than the current state-of-the-art method of bonding AUCTs with epoxy glue.However, this study is limited to a particular type of epoxy film adhesive and special state-of-the-art PCT transducers. Although they represent the state-of-the-art, it may be possible that other types of epoxy adhesives and PCTs may have better or worse performance in the AOEC tests performed in this study. This study could be extended to other types of adhesives to establish if the TPFs have better performance with respect to other adhesives or not. In addition to EMI methodology employed in this study to measure the changes in the AUCT characteristics, other methods, such as changes in the guided wave signals and out-of-plane velocity, could be performed, which can give more insights into the changes that can occur in the adhesive layer and the AUCT characteristics during the AOEC tests.In the current study, the AUCT have been bonded to the composite specimen by oven heating and vacuum bagging. This process can be time-consuming and may require heating the entire structure, which can cause thermal degradation to the structure. To overcome these drawbacks, an easier, faster, and economic method of bonding AUCTs to TP composite structure using local induction heating is currently being investigated by the authors. Furthermore, it is very important to study the mechanical performance of the selected TPFs as compared to the epoxy adhesives used to bond the AUCTs. Therefore, the mechanical performance of the AUCTs bonded with the TPFs with oven and induction heating will be studied in great detail through different mechanical tests, such as tensile-tensile fatigue and static and cyclic flexural tests, and compared with that of the epoxy adhesives.


This study proposed a strategy for a quick fault recovery response when an actuator failure problem occurred while a humanoid robot with 7-DOF anthropomorphic arms was performing a task with upper body motion. The objective of this study was to develop an algorithm for joint reconfiguration of the receptionist robot called Namo so that the robot can still perform a set of emblematic gestures if an actuator fails or is damaged. We proposed a gesture similarity measurement to be used as an objective function and used bio-inspired artificial intelligence methods, including a genetic algorithm, a bacteria foraging optimization algorithm, and an artificial bee colony, to determine good solutions for joint reconfiguration. When an actuator fails, the failed joint will be locked at the average angle calculated from all emblematic gestures. We used grid search to determine suitable parameter sets for each method before making a comparison of their performance. The results showed that bio-inspired artificial intelligence methods could successfully suggest reconfigured gestures after joint motor failure within 1 s. After 100 repetitions, BFOA and ABC returned the best-reconfigured gestures; there was no statistical difference. However, ABC yielded more reliable reconfigured gestures; there was significantly less interquartile range among the results than BFOA. The joint reconfiguration method was demonstrated for all possible joint failure conditions. The results showed that the proposed method could determine good reconfigured gestures under given time constraints; hence, it could be used for joint failure recovery in real applications. Recently, a greater number of social robots have been introduced to the service industry. Anthropomorphic or humanoid social robots were designed and developed to attract special attention from human users. An anthropomorphic robot arm allows design flexible movement that can be easily adapted to various situations. A human arm can be modeled as a 7-DOF kinematic model ; thus, aSince 2010, the humanoid receptionist robot called Namo, which was developed by the Institute of Field Robotics, KMUTT, has provided services for different social functions such as opening ceremonies, fashion shows, etc. . Namo haOne way to handle the problem of some actuators malfunctioning is designing and developing robots with redundancy mechanisms ,5,6,7,8;The concept of using redundancy in robots became commonly applied. Instead of using complex computation to reconfigure the remaining joints, another approach to handling the failure recovery problem is using soft computing techniques ,13. NatuFrom the literature, the strategy for robots to recover from joint failure is using redundant design and then performing computational reconfiguration of the remaining functional joints to cope with the failed joint. Inverse kinematics ,21, quadNamo is a semi-humanoid receptionist robot, as shown in Each arm has seven degrees of freedom. The actuators are located on Namo’s arm, as illustrated in Unlike joint failure recovery for robot manipulators, joint failure recovery for humanoid receptionist robots requires not only the correct end-effector position but the overall robot arms’ positions must also represent the correct emblematic gestures; the output combination of elbow, wrist, and palm positions should be perceived by humans as emblematic gestures. We proposed a gesture similarity measurement to be the measure for evaluating the similarity between the new joint configuration and the original configuration for each gesture. The gesture similarity score consists of four weighted terms from four components of the arm, including the elbow, wrist, fingertip, and palm orientation, as inp, and that of the reference hand, q. Then, ds is the angular distance between the reconfigured hand orientation and the reference hand orientation.For the hand orientation, we used the distance between rotation quaternions instead. Assuming that the reconfigured wrist is at the same position as the reference wrist, as illustrated in wrist_LR, and the distance between the fingertip of the left and right hands, dtip_LR, in the gesture similarity measurement, asoffset is the offset value for the thickness of the hand. In this study, the weight values for (1) and (2) were set as equal weight values for all components.For Wai, both of Namo’s arms need to be in the correct position in order to represent the Thai greeting properly. Therefore, we added two more components in (1) to include the distance between the wrist of the left and right hands, dTo solve the problem of joint failure recovery for humanoid receptionist robots, the method should find the reconfigured joint angles of the remaining joints that allow the robots to perform emblematic gestures; the output gestures may not be completely the same as the reference gestures but still communicate the meanings of those gestures. Similar to the way that animals adapt themselves to walk after a leg injury, bio-inspired artificial intelligence methods simulate self-organized mechanisms occurring in nature and use them to solve complex optimization problems . In thisOnce that joint failure occurs, the robot cannot control the failed joint to a desired angle. In this study, we proposed to lock the joint at a specific angle. We determined the locked angle by averaging the joint angles of that failed joint from all reference emblematic gesture sets; the average joint angle could potentially be a less restrictive constraint to the robot system to regenerate a good gesture reconfiguration of the remaining joints for all emblematic gestures. Under the constraint that the joint angle of the failed joint is locked at a specific angle, the bio-inspired artificial intelligence methods, e.g., genetic algorithm (GA), bacteria foraging optimization algorithm (BFOA), and artificial bee colony (ABC), are used as optimizers to generate joint angle sets of the remaining joints and determine a good joint reconfiguration solution that minimizes the difference between the reconfigured gestures and the reference gestures. The similarity to the reference gesture set is the objective function for the joint failure recovery problem; the greater similarity indicates the better joint reconfigured solution. We used the proposed gesture similarity measurement in (1) as the fitness evaluation of the generated joint reconfiguration. After running iterations of bio-inspired artificial intelligence methods, the reconfigured gesture sets were obtained. We demonstrated the performance of the bio-inspired gesture reconfiguration method with three techniques: GA, BFOA, and ABC. We explored the differences in using different techniques for the same failure recovery problem on the Namo robot. The locked joint angle for each of the joints that are averaged from the reference gesture can be expressed in The GA was inspired by the evolution of life in nature. Each chromosome has genotypes that can be expressed to the phenotypes of the lifeform. Through natural selection among the population of lifeforms, better individuals can exist, mate, and reproduce new offspring. The chromosomes of the new offspring can inherit some of their parents’ genotypes through the crossover process and may have some deviated genotypes from the parents through the mutation process. With a number of generation cycles, it is possible that the offspring from the later generation can evolve to survive in the environment better than their ancestors. GA simulates such an evolution process and uses the process to solve many complex problems ,28,29,30In this study, the genetic representation of the chromosome is set as a sequence of 6 real-valued numbers, which correspond to the 6 remaining joint angles to be reconfigured. A population of chromosomes was randomly generated with uniform distribution. The parents for crossover operations were chosen at random. We chose a one-point crossover for this problem. The population in the next generation was reproduced by generation rollover, where the new, better offspring replaced the worst individuals. The key parameters that regulate the evolution process for GA include the population size, crossover rate, mutation rate, mutation step size, and the maximum number of generation cycles.E. coli and M. xanthus bacteria [BFOA was inspired by the foraging behavior of bacteria . With chbacteria . They cabacteria ,34 have bacteria .Similar to the GA algorithm, each bacterium is a sequence of 6 real-valued numbers. The control parameters for BFOA include the population size, the number of chemotactic steps, the swimming length, the number of swim steps, the number of elimination–dispersal events, the number of reproduction steps, and the probability of elimination. Additionally, the control parameters for the swarming dynamics of the bacteria population that should be set appropriately to the application include the depth of attractant released by the cell, the width of the attractant signal, the height of the repellant effect, and the width of the repellant effect.ABC was inspired by the foraging behavior of honey bees . During The dimension of the search space in this problem is 6 according to the 6 remaining joint angles to be reconfigured. Each employed bee represents the solution or food source location in the search space. The best solution has the minimum difference from the reference gesture. The control parameters for ABC include the number of employed bees, the limit number that employed bees will search until abandoning the area to explore other areas in the search space, and the maximum number of cycles. Note that ABC uses the same number of employed bees for onlooker bees at the hive. While employed bees exploit the food source area that they found, onlooker bees can be recruited to explore the adjacent area from the food source the employed found.In this study, we used bio-inspired artificial intelligence algorithms, including GA, BFOA, and ABC, for joint reconfiguration after a joint failure of a service semi-humanoid robot with redundant manipulators to maintain its emblematic gestures. To be used instead of using complex, time-consuming computation of inverse kinematics, the bio-inspired joint reconfiguration results must be within the acceptable difference from the reference gestures; in addition, the computation time must be low enough to allow quick maintenance so that the service robot could continue her duty. All the experiments were run on a computer with a 12th Gen Intel (R) Core (TM) i7-12700K (5 GHz) with 64 GB RAM, running on Ubuntu 22.04 with Visual Studio Code IDE, implemented with Python 3.9 and NumPy 1.20.3.We performed a grid search on varying control parameter values of each algorithm on the Wai gesture in order to determine a good combination of parameters that yields the minimum gesture difference from the reference gesture within 1 s of computation time for joint reconfiguration. We conducted an experiment in the case where Joint 2 failed as an example in this study. The tuned parameter sets given the maximum similarity gesture for GA, BFOA, and ABC are reported in We used the tuned parameter sets of each algorithm for emblematic gesture reconfiguration on the Namo robot when Joint 2 failed to function. The experiment was repeated 100 times in order to test if the tuned parameter sets could be used for other emblematic gestures. The resulting gesture similarity measurement to the reference gestures and resulting computation time are reported in p = 0.000), except for the Wai gesture for which BFOA and ABC did not show the difference (p = 0.072). On the other hand, the Mann–Whitney test on computation time suggested that all algorithms’ solutions returned with distinct computation time from other algorithms’ solutions (p = 0.000), except for the Salute and Side Invite gestures for which BFOA and ABC did not show the difference . BFOA used the lower computation time to yield the solutions in most cases, as shown in The tuned parameter sets from performing a grid search on joint reconfiguration with the Wai gesture can be used for other gestures as well. Using the Kruskal–Wallis test, it can be concluded that using different algorithms demonstrated significantly different effects on gesture similarity and computation time for joint reconfiguration. Compared to other algorithms, after 100 repetitions, ABC resulted in the best values in many aspects. ABC yielded lower difference values from the reference gestures, except for the lowest difference in the Salute gesture; however, the values are not significantly different. ABC produced more reliable results, as shown in As gradient-based optimization algorithms are also found to be efficient for solving inverse kinematics problems, we verified that the chosen optimization methods could perform better than gradient-based algorithms. We compared the performance of emblematic gesture reconfiguration when Joint 2 failed to function for the Wai gesture between using the gradient descent optimization algorithm with momentum  and the It is interesting to investigate whether the tuned parameter sets from one scenario can be extended to use in other joint failure scenarios. In this experiment, we used the tuned parameter sets from Joint 2 failure to reconfigure joint angles after the failure of all possible joints. p = 0.000 and p = 0.000, respectively). Between the BFOA and ABC pair groups, the Wilcoxon matched-pairs signed-rank test did not show significant differences in the minimum difference values (p = 0.399). When considering the algorithm performance on the reliability of the results, the Wilcoxon matched-pairs signed-rank test showed significant differences in median difference values and the interquartile range of resulting difference values between BFOA and ABC (p = 0.000). Hence, it may be concluded that BFOA can provide a chance to yield better joint reconfiguration, but ABC can be relied upon for determining good joint reconfiguration.The results showed that the best reconfigurations, which are the reconfiguration with the minimum difference value, from BFOA and ABC, were significantly better than those from GA . Joint 3 is responsible for the control of the lower arm from the elbow to open or close (or rotate around the z-axis). When joint 2 or 3 fails and is locked at the averaged angle from all the reference gestures, the space for the robot hands to reach and join together at the chest area is limited. The joint reconfiguration method has attempted to determine a good solution with low gesture difference values, but the locked joint angle at the averaged angle from all reference gestures seemed to limit the search space. In our future study, we plan to include the locked joint angle in the problem so that the joint reconfiguration method can determine a good joint angle to lock the failed joint and may allow better-reconfigured gestures than the output in this study.From the gesture similarity measure, the failure at one joint position could contribute to the difficulty of joint reconfiguration on each emblematic gesture differently. The best gesture difference values for the Wai gesture in Considering the resulting gesture similarity measurement from all possible joint failures, we found that the strategy to lock the failed joint at some specific joint angle had an immense impact on the success of performing the emblematic gestures. The average joint angle from all gestures may not always be suitable. We analyzed the distance of each component of the robot arm in all best-reconfigured gestures when each failed joint occurred. Joints 1–3 are located in the shoulder area and are designed to control the movement of the robot’s upper arm. Joint 1 is responsible for controlling the upper arm to swing forward and backwards. Joint 2 controls the upper arm to swing up and down to the side of the robot. Joint 3 controls the upper arm to rotate inward and outward from the robot’s body. When one of these joints fails, it affects all the components along the arm. The results in Although we can employ the bio-inspired AI technique to determine a good solution to control other functional joints to compensate for the failed joint that was locked to a specific angle, the compensation from other joints might not be enough to recover from the failure for performing some gestures if the locked joint is not suitable. Joint 4 is located at the elbow and controls the movement of the lower arm upward and downward. When Joint 4 fails, the methods can determine good solutions with minimal difference values compared to when other joints fail, as shown in Joints 5–7 are located at the wrist area and are designed to control the movement of the robot’s hand, including the palm orientation. The Wai gesture is a good example of the performance of joint reconfiguration when the joints in this area fail. From the results of all possible joint failures, it can be concluded that the strategy to set the joint angle to lock the failed joint is another issue that should be considered for joint reconfiguration to recover from joint failure.In this study, we proposed gesture similarity measurement for semi-humanoid robots performing emblematic gestures and proposed the use of bio-inspired AI techniques for joint reconfiguration to recover from joint failures within a given time constraint. We explored the performance of the joint reconfiguration method with a strategy that used the average values of joint angles from all gestures as the locked angle for the failed joint. We found that the joint reconfiguration method using bio-inspired AI techniques could determine good reconfigured gestures for the robot. The results suggested that ABC and BFOA have the potential to generate the best-reconfigured outputs within 1 s of computation time, which allow quick maintenance in real applications. From 100 repetitions, ABC showed the higher reliability of the results with less interquartile ranges of the results in all emblematic gestures.By analyzing the distance between the reconfigured gestures and the reference gestures, we realized that the intuitive strategy, which uses the average values from joint angles of all emblematic gestures the robot performs as the locked angle for the failed joint, was not suitable for performing all emblematic gestures as expected. In the future, we plan to improve our joint reconfiguration method using bio-inspired AI so that the method could suggest a suitable locked angle for the failed joint as well. Nevertheless, having just one reference joint angle set for each emblematic gesture may result in difficulty in determining a suitable locked angle for all gestures. As humans, each of us performs gestures differently; we plan to explore the idea of using multiple reference joint angle sets for each gesture to aid joint failure recovery in humanoid robots performing emblematic gestures.


Selenicereus undatus is a hemi-epiphytic root climber that attaches itself to supporting plants or rocks with adventitious roots. The anatomy and biomechanics of the adventitious roots were studied using light microscopy, X-ray tomography and pullout and uniaxial tensile tests. The central cylinder of the roots is highly lignified and is connected to the vascular system of the shoot in a peculiar way. Xylem elements of the root turn 90 degrees towards the base of the shoot and merge laterally and below the junction with those from the shoot. Tensile and pull-out tests showed that failure occurs either at the root or junction, with the fracture surface mainly comprising the area where xylem elements from the root merge with those from the shoot. However, damage to the cortical tissue was minimal, and the measured forces showed that adventitious roots have a high safety factor. Even a complete failure of the junction after pullout does not result in severe injury to the cortex, which could lead to water loss or the entry of pathogens.Cacti have a distinct adaptation to arid conditions with a massive water storing tissue surrounding a weak central woody cylinder. However, they have not been studied as extensively as other plants have been.  The (hemi)epiphytic life form is generally applied to plants structurally depending on other plants as substrate. Roughly 9% of vascular plants are considered to be epiphytes although the exact use of the term is not always straightforward. There is an accepted distinction between holo-epiphytes that spend their whole life cycle on the supporting plant and hemi-epiphytes that root in the soil at least during some growth stages. Additionally, the terms “nomadic vines” and “aerial hemiparasites” have been proposed for plants such as lianas and mistletoes, respectively ,2,3,4. ASelenicereus undatus (Haw.) D.R.Hunt (syn. Hylocereus undatus) is a root-climbing species amongst a small number of (hemi-) epiphytic Cactaceae [Selenicereus setaceus [Opuntia ficus-indica, Cylindropuntia bigelovii and H. undatus as well as for flowers in H. undatus [actaceae   individual roots lose contact to their substrate, which we do not consider here; (2) root breakage occurs in between shoot surfaces and the point of attachment to the substrate; or (3) in the worst case, pull-out of the root occurs from the shoot at the junction. The latter failure mode could eventually cause massive damage to the xylem and the water-storing primary cortex, and, as a result, attack by pathogens.Generally, obtaining entire unfragmented sections of root material is difficult. Although adhesive tape helps to stabilize the root during cutting and staining, the connection between the pith and xylem is fragile and fragments easily, as does the cambial area between the xylem and bast. Through a top view of a cross-section of a root, however, all parts were observed to be connected.Selenicereus setaceus shoots [Ferocactus acanthodes, Pilosocereus pachycladus and Opuntia basilaris, but with an unlignified pith [The cross-section exhibited the general arrangement of tissues characteristic of aerial roots, with a central cylinder enclosing a pith, small amounts of phloem located at the end of rays separating xylem poles and a primary cortex presumably covered by a rhizodermis in early stages of development. The latter, however, is already replaced very early on by secondary tissues, including the bast, that most likely forms as a kind of sheath acting as a protective barrier against desiccation during root growth. This would also explain why it is found only on the root part extending outside of the shoot but not within the shoot cortex. These tissues were dead in almost all samples, with collapsed parenchymatous tissue alternating with fibers, comprising a structure similar to the bark structure described for s shoots . A similied pith ,19,20,21The separation of the inner and outer fiber bundles, clearly visible in the X-ray tomography sample B, can alS. setaceus, the whole shoot was modified according to the mechanical needs from almost self-supporting basal parts to searchers looking for new support in tree crowns or hanging over rocks [It remained unclear from the roots studied whether the lignified rays between the xylem poles in younger roots  or a characteristic of the species. Considering the variable number of roots per shoot, a mechanism to start the root growth has to exist, for which factors still have to be identified. Based on the limited significance of the observations in the greenhouse, adventitious roots seem to be produced primarily on shoots that grow upwards or horizontally, while they are lacking on shoot sections that hang down. The complete lignification of the central cylinder including the pith and the way the fibers are connected to the shoot point towards a primary function of the roots as anchoring structures, although observations in the literature suggest the possibility of a nutritional function if the soil is reached . The ressame way , althougThe difference in breaking force for root failure in pull-out and tensile tests and junction failure can be explained from a structural point of view. In the tensile test, the force acts along the fiber orientation, i.e., the direction in which the highest tensile load can be applied. The differences in the recorded forces in the two different test modes are mostly explained by the fact, that in the tensile tests, selected short, straight segments of the root were used, while in the pull-out tests, the roots showed various amounts of curvature. These roots were straightened in the beginning, which most certainly caused pre-damage to the material, and therefore failure at lower forces.In the pull-out test, the force was transferred through the junction to the fibers running along the axis of the central cylinder which were then stressed perpendicularly to their preferred direction. The shape of the fracture surface is due to the difference in fiber connection to the central cylinder. On the shoot’s abaxial side, the fibers are only bent around one corner. On the adaxial side, the fibers are led back in a basal direction and thus around two corners, which increases the stresses acting in the junction. In addition, these fibers have only few connections to fibers of the wood cylinder running further up the shoot. There is almost no lateral connectivity to the fibers in the shoot xylem so acting forces are only transmitted along one axis but not around its circumference as it was observed in the connection between the shoots and flowers or branches via the areoles . As a reThe maximum recorded forces for failure do not take into account the different individual values for the diameter or cross-sectional area of the central cylinder of the roots. However, this is the most suitable way to test the biological function of the mechanics of root attachment. The breaking stress allows a comparison of the tensile tests and those pull-out tests in which the root failed, but not of those where the junction failed. Here, the fracture surface is irregularly shaped and the failure mode different, not allowing to compare Young’s moduli or breaking stress adequately. It should be generally noted that the calculation result of the fracture surface area from pictures is an underestimation, as the fracture surface is not flat but domed, and that the root base radius is an overestimation of the radius of the mechanically relevant cross-section, as the bast adds a non-negligible thickness. Still, the breaking stress calculated with the root base diameter showed significant differences between pull-out and tensile tests. These should follow the same explanation as that for the differences between the breaking forces. The difference in Young’s modulus is primarily caused by a structural difference between the samples in the pull-out and tensile test. In the pull-out test, the forces act on the junction first and thus on fibers running perpendicular to the force direction. In the tensile test, the forces act parallelly to the fiber direction.The force necessary for a failure, either along the root or in the junction, shows that the aerial root attachment is developed in such a way that it possesses a high safety factor, which is common in plants . The aveThe pull-out test indicated a lower breaking force for root failure than that for junction failure, in opposition to the tensile tests. Since root failure in both cases should follow the same mechanism, the explanation for the difference most likely is pre-damage during the straightening of curved roots. However, even if the root is pulled out of the shoot, causing considerable damage to the wood cylinder, the damage in the primary cortex of the plant including the epidermis is surprisingly limited to the diameter of the root. There seems to be no strong connection between the root material and the cortical cells of the shoot, which limits the damage to the shoot xylem, minimizing water loss from a wound or the probability of pathogens penetrating the cortical tissue.S. undatus. These are the exact processes of root initiation and early development towards a non-nutritional root on a cellular level and how the roots anchor themselves to their substrate as well as the exact mechanism through which damage is avoided in the cortex and epidermis of the shoot. For a better general understanding of Cactacea anatomy, the aerial roots should also be compared to below-ground roots.Important aspects still need to be studied to understand the mechanisms of the aerial roots of Plant material was taken between February and May 2022 from a plant cultivated at the Botanical Garden of Technische Universität Dresden, Dresden, Germany, in the desert greenhouse under seasonal conditions A. The plAll shoot samples were measured in length and weighed before further processing. The sampled shoots weighed between 2–3 g/cm and had a length of 15–60 cm. The number of fully developed aerial roots per shoot section was highly variable; some sections had none, while others had more than 20, with a diameter of 0.7–2.7 mm measured just above the shoot surface and a length of 30–200 mm.For the preparation of root cross-sections, shoot sections with roots were cut and embedded in polyethylenglycol 4000 . The parenchymatous ribs had to be cut to fit into the embedding container. All root sections were prepared from root parts from in between 5 to 20 mm measured from the shoot surface. Sectioning was carried out on a sliding microtome  with a slice thickness of 10–30 µm. To stabilize the fragile sections, the block surface was covered in adhesive tape  before each cut ,29,30. SFor X-ray tomography, shoot samples were macerated in cold water for roughly one week until the central cylinder and woody roots could be isolated via careful rinsing. The central cylinder was subsequently airdried for several days, then finish-dried at 60 °C in a drying cabinet  and sawed into sections of ~15 mm length with one aerial root each. Tomography measurements were carried out on ProCon CT-XPRESS  and analyzed using the software Dragonfly 3.5 . Segmentation was performed manually. Additional images of macerated samples were taken on a Zeiss Supra 40 VP scanning electron microscope .Tensile tests were performed on a total of 11 isolated aerial root samples and pull-out tests were performed on a total of 52 roots still connected to the shoot, using a universal testing machine and corresponding software . Only fully developed roots, as determined according to the dried-out root tips, were used. For pull-out, tests the free root ends were glued onto paper strips with cyanoacrylate glue  to prevent slipout from the clamps during testing. Subsequently, the root was lead through a 20 mm hole in a fixed aluminum plate of a 10 mm thickness to ensure that the junction was not influenced by clamping forces during testing. The sample diameter was measured using digital calipers  at the sample’s center or at the contact point of the root and shoot surface for tensile and pull-out testing, respectively. The free sample length was chosen to be 40 mm, the pre-load was chosen to be 0.1 N and the testing speed was chosen to be 2 mm/min. The force was applied in line with the root. The resulting elongation was recorded from the traverse movement and the resulting force was recorded with a 5 kN load cell . The software OriginLab 2021 Pro  was used to calculate characteristic biomechanical values and compare them statistically using a Kruskal–Wallis ANOVA and Dunn’s test at a significance level of 0.05. For the sake of comparison, the root cross-section was used to calculate all normalized values. The cross-sectional area of pulled out junctions was calculated with the software ImageJ  from pictures taken after testing.