Extracelluar matrix (ECM) proteins create complex networks of macromolecules which fill-in the extracellular spaces of living tissues. They provide structural support and play an important role in maintaining cellular functions. Identification of ECM proteins can play a vital role in studying various types of diseases. Conventional wet lab–based methods are reliable; however, they are expensive and time consuming and are, therefore, not scalable. In this research, we propose a sequence-based novel machine learning approach for the prediction of ECM proteins. In the proposed method, composition of k-spaced amino acid pair (CKSAAP) features are encoded into a classifiable latent space (LS) with the help of deep latent space encoding (LSE). A comprehensive ablation analysis is conducted for performance evaluation of the proposed method. Results are compared with other state-of-the-art methods on the benchmark dataset, and the proposed ECM-LSE approach has shown to comprehensively outperform the contemporary methods. Extracelluar matrix (ECM) is a network of fibrous proteins filled in the extracellular spaces of living tissues to provide structural support for the cells . The cheFunctional research on ECM protein has resulted in the development of useful biomaterials which are used in many fields of medicine, such as tissue engineering and cell therapy (in-silico approach to predict the extracellular proteins was presented by The first benchmark k-spaced amino acid pair encoding. A latent space representation of composition of k-spaced amino acid pairs (CKSAAP) is learned which can help to design a robust classifier. This eliminates the need for separately developing the classifier and the feature extraction modules, and a stand-alone model effectively learns the distinguishing characteristics of classes on a lower dimensional feature space.Development of a feature space and selection of the best features are fundamental steps in designing machine learning models . In partThe rest of the article is organized as follows: the classification framework of the proposed method is presented in For proper evaluation of the proposed model, a number of standard performance metrics have been used. The most intuitive performance measure is accuracy; however, for a highly imbalanced dataset (which is the case here), accuracy is not reflective of true performance. Therefore, various evaluation parameters, such as sensitivity, specificity, and Matthew’s correlation coefficient (MCC) are reported. Youden’s index and balanced accuracy are also considered to be important evaluation metrics for imbalanced data and are, therefore, extensively explored in this research.% or higher similarity.To design the proposed method, we used the benchmark dataset provided in One of the fundamental steps in designing a machine learning approach is the transformation of protein sequences to a numerical format. Several methods of this transformation exist and the resultant encoded vectors of the sequences are treated as the features. The common approach practiced by several researchers is to acquire various features of the same sequence by employing different encoding schemes, and their combination is utilized for training the machine learning algorithm. This laborious approach has resulted in the performance enhancement of some classifiers ; howeverk-spaced amino acid pairs in the protein sequence. Each k-spaced amino acid pair represents the residue pair separated by any arbitrary number k  of amino acid residues. For k = 0, the encoding is similar to the DPC, in which protein sequence of 20 types of amino acids yields a feature vector of (20 × 20) = 400 types of amino acid pairs 400. In earlier studies it has been suggested that the DPC and higher-order peptide features can be used to design a robust protein sequence classifier  × 400. The graphical representation of the CKSAAP feature vector obtained with k = 2 has been depicted in The CKSAAP scheme works on the simple principle of counting the occurrence frequencies of assifier . From Fik value. In this research, we aim to find the optimal value of k by analyzing different combinations of the features generated by CKSAAP, and details are presented in This efficient method of encoding has, therefore, been favored by a number of researchers in various applications of computational biology including the prediction of anticancer peptides , DNA, ank, which is expected to result in a more robust model  classifier for the latent space encoding based on an auto-encoder. Latent space refers to the representation of compressed data in which similar points would be in a close group, as shown in The architecture of the proposed ECM-LSE network is composed of two modules: 1) an auto-encoder module and 2) a classification module.% dropout, and a rectified linear unit (ReLU) activation function. The latent space layer uses sigmoid activation function without any batch normalization and dropout.The auto-encoder is a type of neural network that can act as an identity function. It is used to find the representation of the input signal in a reduced dimensional space, known as the latent space. The principle of latent space–based representation is an assumption that the input signal has a low-rank. The auto-encoder network has a decoder that tries to regenerate the input from the latent space variables. During the training of an auto-encoder, the model is forced to become an identity function. Due to which only the relevant features of the data are learned in a compressed representation. This compressed representation has sufficient information for accurate reconstruction of the original input signal. The number of hidden layers and the number of neurons in each layer of the encoder and decoder are varied to obtain reasonable performance. In this research, the encoder and decoder are composed of three layers each, including two hidden layers. The number of neurons in the input layer of the encoder is equal to the length of the attribute vector. The number of neurons in the first and second hidden layers is set to be 50 and 10, respectively. The decoder is a mirror symmetry of the encoder. The number of neurons in the output layer of the decoder is equal to the length of the attribute vector. The number of neurons in the latent space is systematically altered to obtain the best performance for which we designed an ablation study discussed in The output of the encoder module (latent variables) is used as an input to the classification module. The classifier module shown in LVs) and the CKSAAP gap value k were evaluated. For each choice of model configuration, the process of model training was repeated 20 times and mean and standard deviations of performance statistics were reported. In each trial, the weights and bias of the model were randomly initialized. Also, each trial utilized randomly configured subsets from the training, validation, and test dataset. The validation process assisted toward the filtration of the overfitted models, that is, only the models with 75% or higher validation balanced accuracy was selected.To develop a neural network model, the benchmark dataset was divided into the train, validation, and test datasets. For training, we formed a dataset consisting of 540 samples with equal number of ECMs and non-ECM protein samples. These were randomly selected from the pool of 445 ECMs and 3,327 non-ECMs, since the available dataset is very small, and it is highly likely that the model would suffer from the overfitting problem. To avoid such situation, we employed regularization techniques such as early stopping, dropout, batch normalization, and DeepLSE-based feature encoding. Furthermore, the validation dataset was also used with the aim of designing a generalized classifier module. The validation dataset consists of 30 ECMs and 810 non-ECMs randomly selected from the remaining 175 ECMs and 3,182 non-ECMs, respectively. The remaining 145 and 2,247 samples of ECMs and non-ECMs were used in the test dataset. Several model configurations on the basis of the latent space size  by a margin of 10.91%. The specificity value achieved by the proposed ECM-LSE also compares favorably with other methods, which confirms the balanced unbiased learning effect. It is noteworthy to point out that the accuracy metric cannot provide true fitness of the models given the skewed distribution of test dataset toward the negative (non-ECM) class. Any model with all negative predictions can achieve % test accuracy, which is 0.17% lower than the PECM, better balanced accuracy and Youden’s index values, which is 3.93% and 0.08 units higher, respectively, demonstrate the superiority of the proposed method. Similarly, the MCC value achieved by ECM-LSE is 7.63% higher than the PECM method. MCC metric is preferred for accuracy and is considered as more reliable statistical parameter because it produces a higher value only if the classifier achieved good results in all four categories of the confusion matrix  correctly identified 19 proteins as extracellular matrix proteins, whereas PECM, ECMSRC, and EcmPred identified 18, 16, and 15 proteins, respectively. It is noteworthy to point out that the models were trained on ECM proteins from metazoans; therefore, the superior performance of the proposed ECM-LSE on proteins from a completely different organism suggests that it can be effectively utilized for the annotation of unknown proteins.To verify the practical usefulness of our method, herein, we perform the validation of our method on experimentally verified ECM proteins. In particular, we collected 20 experimentally verified human ECM proteins from UniProt . The colFor typical classification problems such as lysine acetylation site prediction in proteins  or the iFor visualization purposes, the data were projected on two dimensions using t-SNE  projectiThe proposed method, as shown in https://github.com/Shujaat123/ECM-LSE/blob/master/ECM_LSE_Online.ipynb). In the future, we aim to explore the efficacy of the auto-encoder–based classifiers on other bioinformatics problems.The proposed hybrid approach presents a hybrid design with capabilities of efficient feature selection and classification of ECM proteins. The latent space dynamically reduces the dimension of the feature space and retains only the relevant information sufficient to efficiently distinguish ECM from non-ECM samples. Although, the proposed method can predict ECM from different organisms, it is not a replacement for gold standard wet lab–based testing. Furthermore, due to the scarcity of available ECM proteins the model may show biased performance in favor of already explored ECM and finding novel proteins may require the fusion of additional information. However, efforts have been made to avoid overfitting in order to seek the generalization property of the model by deploying dropout and batch normalization techniques. Further enhancements to the ECM prediction task where scarcity of the positive samples persists can be made by applying a transfer learning approach, where a large scale model is trained on a closely related dataset and is further fine-tuned for ECM samples. The Python implementation of the proposed algorithm has been made public, and interested users can utilize the algorithm for their problem of interest. The algorithm is available at (% with 0.71 Youden’s index and 0.39 MCC (with k = 8 and LV = 7). Additionally, the model performance is verified on completely unseen experimentally verified ECM proteins and shown to achieve highest prediction score.ECM is a complex meshwork of cross-linked proteins responsible for the architectural support of cells and contributes to the functionality of the living tissue. They also contribute toward the formation of the cancer stem cells; therefore, their study and classification from non-ECMs proteins is of prime importance. A reliable prediction method can not only help understand various abnormalities associated with several cancer types but will also assist in diagnostic research. Conventional experimental-based methods are considered gold standards for this task; however, they are extremely time consuming and scanning a large number of proteins is practically infeasible. In this research, we designed a latent space learning method for the classification of ECM proteins. The proposed method can be used as a reliable prediction model. An important feature of the proposed method is its latent space-based projections through which protein sequences can be visualized in filtered and reduced dimensions, which is extremely helpful in finding useful clusters. The proposed method has been tested on a benchmark dataset and results of widely used performance metrics are reported. In particular, we report a balanced test accuracy of 86.45


To these cysteines, as well as to several native lysine side chains, the photoinduced redox label 8-thiouredopyrene-1,3,6-trisulfonate (TUPS) was covalently attached. The long-lived, low potential triplet excited state of TUPS, generated with high quantum efficiency, serves as an electron donor to the oxidized heme c. The rates of the forward (from the label to the heme) and the reverse (from the reduced heme back to the oxidized label) electron transfer reactions were obtained from multichannel and single wavelength flash photolysis absorption kinetic experiments. The electronic coupling term and the reorganization energy for electron transfer in this system were estimated from temperature-dependent experiments and compared with calculated parameters using the crystal and the solution NMR structure of the protein. These results together with the observation of multiexponential kinetics strongly support earlier conclusions that the flexible arm connecting TUPS to the protein allows several shortcut routes for the electron involving through space jumps between the label and the protein surface.Electron transfer within and between proteins is a fundamental biological phenomenon, in which efficiency depends on several physical parameters. We have engineered a number of horse heart cytochrome  Electron transfer involving various metabolites, external electron sources, and redox cofactors of proteins is a fundamental process in all domains of life on Earth. A major focus of research in biological electron transfer has been directed towards understanding how the distance that separates redox active centers in proteins and DNA and the molecular structure of the separation medium influence the electron transfer rates, which must be fast enough for physiologically relevant processes. Early studies of electron transfer in the photosynthetic reaction center  yielded Examination of the electron transfer mechanisms in proteins requires high time-resolution spectral measurements. Chemical modification with ruthenium complexes has allowed investigators to also examine, in non-photosynthetic proteins, the dependence of the electron transfer rate on the distance separating two, natively occurring and chemically introduced, redox centers ,6. Howevc is a relatively small, globular, heme containing redox protein. The distance from any point on the surface of the protein to the heme and the rather uniform protein packing are in the range where electron transfer can take place at an acceptable rate. Nevertheless, electron transfer between cytochrome c and its physiological partners, the cytochrome 1bc complex, cytochrome c peroxidase, and cytochrome c oxidase, takes place after appropriate docking with the positively charged face of cytochrome c where the edge of the heme is exposed  .Data analysis, including the fit of the data matrices by the base spectra of the pure forms, the multiexponential fit of the kinetic traces, as well as fitting the kinetics by the reaction scheme  were perT*) production, and the low reduction potential of the triplet. On the one hand, the flexibility of the linker connecting TUPS to amino acids (lysine or cysteine) allows the mobility of the dye to the extent that it is not possible to assign the entry point of the electron to an exact location on the protein surface. On the other hand, our experiments and calculations show that electron injection by TUPS into the heme can be much faster than expected from the distance or connectivity based on the position of the amino acid to which the dye is attached. This is a clear advantage when TUPS is used to initiate intraprotein or interprotein electron transfer in more complex systems than cytochrome c alone. Indeed, electron transfer was successfully characterized between internal cofactors by TUPS-labeled cytochrome c in complex with cytochrome c oxidase, and the flavin cofactors in the more complex TUPS-labeled enzymes, cytochrome P450 reductase (CPR) and the reductase domain of neuronal nitric oxide synthase (nNOS) [The advantages of using TUPS to study electron transfer lie in the relatively easy chemistry to achieve singly labeled pure protein samples, the high quantum efficiency of the excited triplet state (TUPSe (nNOS) ,15,38.


Bolted joints are fundamental to numerous structural components in engineering practice. Nevertheless, their failure or even their loosening can lead to insufficient performance and reduced structural safety. This study presents a theoretical development and experimental investigation into nonlinear guided-wave mixing for integrity monitoring of bolted joints in plates. Combinational harmonics generated due to nonlinear Lamb wave mixing and contact acoustic nonlinearity at the bolted joints were used to evaluate the applied torque level in the joint. The area of the power spectral density in the region of the sum combinational harmonic bandwidth is found to be highly correlated to the applied torque level at the joint. Moreover, the effect of the number of cycles and thus the time duration of the excitation is investigated. The results show that the combinational harmonics remain robust for different numbers of cycles in detecting bolt loosening. The findings presented in this study also provide physical insight into the phenomena of nonlinear Lamb wave mixing for evaluating applied torque in bolted joints, and the results help further advance the use of nonlinear guided waves for damage detection. To evaluate changes in structural performance, the capabilities of both structural health monitoring (SHM) and non-destructive testing (NDT) have been joined to be developed and implemented in real structures. Integrity and safety are paramount to any structural components; hence, there is great interest in early damage and degradation detection. Bolted structural connection is an efficient and versatile connection technique widely used in various engineering structures such as bridges , wind tuA direct approach to monitor bolted joints is through the installation of load cells or strain gauges at the bolts. However, this approach requires as many load cells as bolts to monitor the bolted connections. This significantly increases inspection and operational cost for structures. Alternatively, indirect methods have also been studied in the literature. Traditional ultrasonic techniques have been investigated for axial force monitoring in bolts ,6. TransContrary to traditional NDT techniques, methods based on guided waves (GWs) have the ability to inspect large and inaccessible areas. They have attracted significant research interest for NDE and SHM in recent years. GWs have the ability to propagate in different types of structural elements, such as beams , bars 11, pipes It was demonstrated that nonlinear features can potentially outperform linear techniques for early bolt-loosening detection. Damage indexes were developed for both linear and nonlinear acoustic/ultrasound approaches, and those were fit by hyperbolic tangent functions . An impaAnalogous to bulk waves, nonlinear GW-based methods have proven more effective compared to linear GW-based methods ,25, withGiven the multimodal nature of guided waves, and the existence of higher-order propagation modes, limited work in the field of nonlinear guided-wave mixing can be found in the literature, aiming at fundamentally understanding the mixing phenomenon as in ,33,34,35Further research is required not only to understand the mixing phenomenon but also to appreciate and benefit from the advantages of nonlinear wave mixing. The need for premature bolt-loosening detection in structures by an inexpensive, reliable, and prompt detection method has motivated this research. Nonlinear guided-wave mixing in bolted structural joints has not been fully investigated in the literature. As such, this study experimentally explores Lamb wave mixing on a steel bolted joint to demonstrate that bolt-loosening effects can be correlated to the combined sum harmonic. Moreover, the use of small and low-cost piezoceramic transducers, instead of traditional ultrasonic transducers, broadens the applicability of the proposed approach to allow integration into in situ NDT and SHM systems. Using nonlinear guided-wave-mixing techniques, the advantages of mid- to long-range inspection would reduce inspection times, resulting in lower related costs, with the added ability to detect early-stage damage ,43. ThisThe paper is organised as follows. The first section provides a theoretical framework for the wave-mixing phenomenon. The following section outlines the experimental setup, in which the specimen is described and the wave-actuation and -sensing approach is presented. The excitation signal selection is described in the next section, following the mechanisms for the applied torque studies. This is followed by the results comparing the signals in the time domain with their limitations and the analysis of the proposed mixed-frequency technique. The effect of the number of cycles is studied next, and this study is then finished with concluding remarks.When an incident GW containing two sinusoidal pulses propagates through a pristine material, the frequency spectrum of the received wave ideally contains frequency components corresponding only to the central frequencies of the two incident sinusoidal signals. However, when the wave travels through a region where a source of nonlinearity is present , higher and combinational harmonics are present in the amplitude spectra of the received wave pulses, in addition to components at the central frequencies of the two incident sinusoidal pulses. The explanation for this phenomenon is that the incident sinusoidal pulses interact with the nonlinearity source and generate the higher and combinational harmonics.aP and bP are the individual forces (with their corresponding amplitudes). aω and bω are the central frequencies, and aN and bN are the corresponding numbers of cycles. t represents the time. The equation of motion of the system can be written as follows [m denotes the mass and φ is used to scale the nonlinear part in the perturbation solution. The bolted joint investigated in this paper is considered as a contact interface whose pressure between contact faces varies according to the applied force between the bolt and nut. A simplified approach is used in this study. We consider the joint behaving as a single-degree-of-freedom system with bilinear stiffness ,44 subje follows :(2)Pacosk1 and k2, respectively. The incident wave would interact with the imperfect contact interface, and the solution to Equation (2) using perturbation theory can be expressed as:ly and nonlinear responses from second and combinational harmonics, shy and chy, respectively. Substituting Equation (3) into Equation (2), we obtain the following relation:The linear and nonlinear contact stiffnesses are represented by (a±b)ω = a±ωbω. It can be seen from Equation (9) that the magnitude of the combinational harmonics is proportional to the nonlinear stiffness k2 and thus related to the applied torque at the bolted joint. The contact mechanism between interfaces during motion generates the contact acoustic nonlinearity (CAN). The amplitude spectra of the response contain three components. They are: (i) the linear component as shown in Equation (7) that is related to the input frequencies; (ii) a nonlinear component as shown in Equation (8) that consists of higher harmonics; and (iii) a nonlinear component as shown in Equation (9) that consists of combinational harmonics resulting from guided-wave mixing. This phenomenon is schematically illustrated in Ignoring the transient components, and making the coefficients equal, linear and nonlinear responses are obtained as below:Es = 205 GPa; density ρs = 7820 kg/m3; and Poisson ratio νs = 0.29. Each plate has three 10 mm drilled holes, and M10 bolts and nuts were used to join the plates with 40 mm overlap. Steel plates were chosen in this study, which are among the most commonly used materials in the civil and mechanical engineering industry. In general, the findings of this study are applicable to other metallic specimens. The experiments for demonstrating the proposed method were conducted on bolted joints composed of two steel plates, with each of them having in-plane dimensions of 200 mm × 360 mm and thickness of 3 mm, as shown in A digital torque wrench, Sidchrome SCMT26952, was used to gradually tighten the bolts. The torque wrench sensitivity was ± 2%. Different torque levels, eleven in total, were applied, and signals were measured at each torque. Minimum applied torque was 20 Nm and maximum was 70 Nm, in 5 Nm steps. Once the eleven levels of applied torque were applied, the bolts were loosened, and the process was repeated for the same eleven levels of the applied torque. The experiment was repeated five times independently. The first part of our analysis is conducted for a single measurement to provide an illustration of the signal quality and the proposed method, and the study finally presents the data for the five independent measures.A circular piezoceramic transducer (PZT) with 5 mm diameter and 2 mm thick was bonded to one of the steel plates using silver conductive epoxy at a distance of 40 mm from the centre of the machined bolt hole. A pitch-catch GW excitation and sensing approach is used in this study. To increase the out-of-plane excitability of the actuator, a brass backing mass was bonded to the top of the transducer using the same conductive epoxy. Another piezoceramic transducer (5 mm diameter and 2 mm thick) was bonded to the other steel plate to receive the actuated wave signal. Using the pitch-catch approach, the signal received by the sensor was expected to carry information from the bolted joint as this signal was generated at the left-hand side of the plate, passed through the bolted joint, and was measured by the sensor located at the right-hand side. A schematic diagram of the actuating and sensing arrangement is shown in An NI PXI-5412 arbitrary wave generator (AWG) was used to generate the excitation signal, which was then fed to a high-power signal amplifier. The signal consists of two sinusoidal tone-burst pulses modulated by Hann windows. These two pulses merged into one signal before sending it to the amplifier. The signal was amplified up to 120 V using a CIPRIAN HVA-400 amplifier and then sent to the actuator. The acquisition was averaged 500 times to improve the signal-to-noise ratio of the measured wave signal. The sensor was connected to an NI PXI-5122 digitiser, and the digitised data were sent to the computer for post-processing. The experimental setup is shown in Two sinusoidal tone-burst pulses with different central frequencies were merged into one single excitation signal before sending to the amplifier. Preliminary tests with single-frequency pulses were first conducted to evaluate the single-frequency response of the piezoceramic transducers. After that, different frequency combinations were examined to find a suitable frequency combination for the tests. Central frequencies of both pulses were chosen so that (i) the sum combinational frequency would not be a multiple of any of the input frequencies and, (ii) the frequency response of the piezoceramic transducers would be optimised. The combinational harmonic investigated in this study is generated by contact nonlinearity at the bolted joint due to bolt loosening. This is not required to fulfil the internal resonance conditions necessary for evaluating material nonlinearity. One of the sinusoidal pulses was at 110 kHz with 10 cycles, whereas the other sinusoidal pulse was at 160 kHz with 14 cycles. Then, both sinusoidal pulses were added together. The number of cycles was selected so that the durations of both single-frequency sinusoidal tone-burst pulses would be the same and have similar energy content.A typical input signal for wave mixing is shown in Signals in the time domain can also be compared to some extent. In However, time-domain features add extra complexity to the data analysis when complicated pulses and wave reflections are involved, especially when the incident wave is not a single-frequency pulse. It is hard to obtain useful information about the bolt condition from the time-domain signals directly. In this study, the data are analysed in a frequency domain. The power spectral density is calculated using the Welch periodogram for each measurement. Using these two scenarios, we can intuitively predict that when the applied torque is increased from 20 Nm to 50 Nm, the contact interface between the washers and the plates also increases. For the case where the bolted joint is tighter at 50 Nm as compared to the case of 20 Nm, the contact effect produced as a consequence of the guided wave travelling through the bolted joint is lesser for the 50 Nm case; hence, the combinational harmonic for the 50 Nm torque is lower than that for the 20 Nm torque. Given the limitations on second harmonic generation already mentioned in the introduction section, such as the small magnitude of the second harmonic and equipment-related nonlinearities, this study focuses on combinational frequency component, specifically at the sum frequency. In this context, we calculate the power of each measurement for every torque value considered. In fact, it can be observed in To further demonstrate the proposed mixed-frequency technique in monitoring bolted joints, the relationship between the applied torque and the areas of power spectral density in the region of the combinational harmonic at the sum frequency within a 32 ± 4 kHz bandwidth were calculated for all five measurements. The averaged values are shown in As described before, when the bolt is tighter, the contact effect decreases. These steadily decreasing values provide a useful understanding of the nature of the combinational harmonic behaviour when a GW passes through a bolted joint, which provides valuable information for the condition of the applied torque. Moreover, the study also shows that the condition of the joint can be assessed by employing two inexpensive piezoelectric transducers without the need for complicated vibration or impact generator equipment.In this section, the effect of the duration/number of cycles of the incident wave is investigated. This study was conducted by increasing the number of cycles of the incident pulses. Apart from the signal studied previously , several different sinusoidal tone bursts were generated and measured by the actuator–sensor pair. The pairs consisted of a 6-cycle 110 kHz signal with a 9-cycle 160 kHz signal, an 8-cycle 110 kHz signal with a 12-cycle 160 kHz signal, a 12-cycle 110 kHz signal with a 17-cycle 160 kHz signal, and a 14-cycle 110 kHz signal with a 19-cycle 160 kHz signal. The numbers of cycles were selected so that both single-frequency sinusoidal tone-burst pulses for each pair would have the same duration and have similar energy content. The area under the curve in the power spectrum within a 32 ± 4 kHz bandwidth was calculated for all five frequency pairs. For each of the five frequency pairs, the calculated area values were plotted versus the applied torque in the same way as the previous section and are shown in A decreasing trend is observed for all five frequency pairs. The proposed technique therefore shows that the applied torque in the bolted joint can be used to monitor the mixed-frequency signals regardless of the employed number of cycles. The trend shifts downwards as the number of cycles increases. The explanation for this phenomenon is that the bandwidth of the signal at the sum frequency component becomes sharper when the number of cycles is increased. In turn, when the frequency component reduces its bandwidth, the area under its curve decreases in magnitude, which shifts all values downwards. This provides a significant insight that even though the proposed monitoring technique is sensitive to the number of cycles, it does not affect its overall performance in monitoring the applied torque using the combinational frequency component.After processing the signal from all five measurements for each frequency pair, the average values with their respective maximum and minimum values were plotted, as seen in With the increasing need to detect structural failures or underperformances in civil and mechanical engineering structures, this study has proposed a nonlinear GW-mixing approach to address the bolted-joint monitoring issue in steel plates. A theoretical development has been presented, according to which the applied torque is correlated to the combinational harmonic at sum frequency due to wave mixing. In this study, a signal containing two central frequency components has been used as input signal. The combinational harmonics at sum frequency are induced by contact acoustic nonlinearity of the bolted joints and have been studied under different levels of applied torque. The results show that the frequency spectra of the measured signals carry information on the bolted joint condition. This study has shown that the mixed-frequency signal is sensitive to the applied torque, and the combinational harmonic at sum frequency increases with a decreasing bolt torque, showing that the early bolt loosening can be detected. This study has also demonstrated the effect of the number of cycles of the incident signal on the combinational harmonic at sum frequency. The results show that the correlation between the applied torque and the combinational harmonic at sum frequency of the GW mixing approach is robust. In addition, by only employing small and inexpensive PZT transducers, this approach could pave the way as a future alternative for online bolted joints monitoring.


To compare the three-dimensional accuracy of an open-tray and two snap on impression techniques (with and without connecting the plastic caps of the snap on impression transfers) in a full arch 6-implant model, a reference acrylic resin model of the maxilla with six implants was fabricated. Prominent geometrical triangles, in the palate area, served as reference points for a digital overlap between scans. Three impression transfer techniques were evaluated and compared: open-tray direct impression (DI), snap on impression (SpO), and connected snap on impression (SpOC). Polyether impression material was used to make 30 impressions (n = 10), and the master model and all casts were digitally scanned with a laboratory optical scanner. The obtained 3D data were converted and recorded as STL files, which were imported to a 3D inspection software program. Angular deviations  between the study casts and the reference model were measured. Data were analyzed using one-way analysis of variance (ANOVA) and Tukey post hoc test, with 0.05 used as the level of significance. The 3D angular deviations from the master model revealed no significant differences between the DI and SpO impression groups, but there were significant differences in the SpOC impression group, particularly in the buccal and occlusal planes. In all groups, the 3D angular deviation between the most distal scan abutments on each side of the model was significantly different from all other areas when compared to the master model. Within the limits of this study, it is possible to conclude that the indirect closed tray snap on impression technique with unconnected plastic caps exhibited the same three-dimensional accuracies as the direct open tray technique. The indirect closed tray snap on impression technique with connected plastic caps was less accurate than either the indirect closed tray snap on impression technique with unconnected plastic caps or the direct open tray technique. In the case of full arch implant supported prostheses, inaccuracies may be expected in the most distal implants for all the three impression techniques evaluated in this study. Further in vitro and in vivo research is required.  The procedure of making an impression is a crucial stage in the implant prosthodontic treatment process, as it directly affects the accuracy of the definitive cast and the passive fit of the implant supported superstructure . A misfiThere are currently two main conventional implant supported impression techniques: the direct technique that uses an open-tray; and the indirect technique that uses a closed-tray . While tPrevious studies have reported that the level of accuracy achieved by the snap on impression method is similar or even higher than achieved by the direct impression method ,17,18. CMost clinicians now agree that the direct technique with splinting of impression copings provides greater accuracy than the non-splinted option, although, other studies have reported no significant differences in splinted versus non-splinted direct methods ,5,21. PaWith the increasing popularity of digital dental technology, in-vitro studies have compared traditional impression procedures with digital impression approaches . While dTo date, very few studies have examined the 3D accuracy of the closed-tray snap on versus the open-tray impression techniques in a full arch model. Moreover, no study has evaluated the impact of connecting the plastic caps on the accuracy of the closed-tray snap on impression technique. The aim of the current study was to compare the three-dimensional accuracy of open-tray and two closed-tray snap on impression techniques (with and without connecting the plastic caps of the snap on impression transfers) in a full arch 6-implant model. The null hypothesis was that there would be no significant differences between the accuracy of these three impression techniques.A custom master model representing a clinical situation of an edentulous maxilla was fabricated from chemically cured methyl-methacrylate . Prominent geometrical triangles were marked in the palate area as reference points for the digital overlap between scans. A milling machine  was used to prepare six parallel, 12 mm long and 4.5 mm in diameter, implant sockets. The holes were located in bilateral symmetry to the midline, with a distance of 10 mm between them. Six implant analogs  were attached to the holes using the same chemically cured methyl-methacrylate . The parallelism of the six analogs was ensured by a surveyor (Surveyor B2 Bio-art). Three study groups were included in this study: the direct impression group  and suitable impression transfers . The impression transfers were screwed to the analogs with 10 Ncm torque, as recommended by the manufacturer, and were connected to each other with transparent self-curing acrylic resin  1 day prior to impression-making. In order to avoid polymerization shrinkage, the connections were thinly sectioned and the transfers were reattached with a thin layer of self-curing acrylic material . One can notice the thin layer of the Pattern resin due to its different color from the transparent acrylic resin. Closed-tray impressions of the master model were made for the SpO and SpOC groups, using stock metal trays and snap on impression transfers . The metal parts of the transfers were screwed to the analogs with 10 Ncm torque, according to the manufacturer’s recommendations. The plastic impression caps were pushed on top of the metal parts until they clicked to ensure a secure fit. The plastic impression caps in the SpOC group samples were connected to each other in the same way as for the DI group. Ten impressions of the master model were taken for each study group, using a one-step monophase technique, with polyether as the impression material . This gave a total of 30 impressions. Following the manufacturer’s instructions, the impression material was allowed to polymerize for 6 min and was then removed from the master model. For the samples in the SpO and SpOC groups, the plastic caps were then picked up and embedded in the impression, while for the DI group, it was necessary to unscrew the transfers in order to loosen them before the impression was removed. Implant analogs  were then snapped into all the transfers and the impressions were poured. The material used was Type IV dental stone  that was mixed in a vacuum mixer , according to the manufacturer’s instructions (100 mg powder/30 mL water). The master model and all study casts were digitally scanned with a laboratory optical scanner  using scan bodies  that were attached to the analogs with 10 Ncm torque, as recommended by the manufacturer. The scan bodies were attached in the same position on the master model as well as on the study models in order to avoid deviations. All obtained 3D data were converted and recorded as standard tessellation language (STL) files, which were imported into a reverse engineering software  for superimposition and 3D deviation assessment. The STL files from the study models were digitally overlapped with the STL file from the master model, which served as the reference data. The superimposition was performed by using the predetermined reference points that were marked on the master model .Three surfaces were defined on each scan body: buccal surface, occlusal surface, and interproximal surface. The 3D deviation measurements were made with the assistance of the computer software, by calculating the angle between each matching scan body surface in the study model compared to the master model. The values of the obtained angles reflect the inaccuracy between the master model and the study models in the three surfaces —buccal. In addition, the accuracy of the position of each scan abutment to its neighbor was also examined on each study model and compared to the master model. For this purpose, each study model was divided into six areas, where area 1 addresses the accuracy between scan abutments 1 and 2 and proceeding to area 6, which considers the accuracy between scan abutments 6 and 1 . The angle between the buccal surface of each scan abutment to the same surface on the adjacent scan abutment was calculated digitally for all study models and then compared to the master model . The buccal surface was chosen as the reference surface for convenience because it has the largest surface on the scan abutment. p = 0.05 was used.Statistical analysis was conducted using a statistical software program . The values of the angles measured on each matching scan abutment surface on all three surfaces in the study model were compared to the master model by using one-way ANOVA. In order to determine which study group was different from the master model, Post hoc Tukey’s tests were used to examine differences between the study groups and the master model. ANOVA with repeated measures; within and between subject factor group and pairwise comparison Bonferroni’s method, were used to examine the accuracy of the position of each scan abutment relative to its neighbor. A significance level of The results of the one-way ANOVA analysis for all three surfaces of the study models and the master model are presented in p = 0.000) and the buccal (p = 0.004) surfaces between all the study models, as compared to the master model. For the interproximal surface, the difference in the angle values showed a weak significance (p = 0.049). Post hoc Tukey’s tests revealed no significant differences between the angle values in the SpO group and the DI groups, for any of the three surfaces  and two closed-tray snap on impression techniques, namely with (SpOC) and without connecting (SpO) the snap on, in a full arch 6-implant model. Computer software was used to calculate the angle between each matching scan body surface in the study model. A comparison between the values obtained and the corresponding angles in the master model provides a measure of the inaccuracies between the master and the study models. The null hypothesis was partially rejected. We found no significant differences between the SpO group and the DI groups in the angles of any of the three surfaces, but the results in the SpOC group were significantly different from the other two groups. This result suggests that the indirect closed-tray snap on impression technique with unconnected plastic caps (SpO) exhibits comparable three-dimensional accuracy to that of the direct open-tray (DI) technique. This is an important point since the DI technique has been extensively studied and found to be the most accurate method for implant impression technique, especially when the transfers were connected by acrylic material ,2,16. OuWhile our results revealed no significant difference in the angle values in the SpO group and the DI group for any of the three surfaces , the angThe significant difference between the SpO and SpOC study groups might be explained by the dimensional inaccuracy of the splinted plastic caps caused by acrylic resin shrinkage. However, the inaccuracy remained even when the connections were severed and the caps were reattached with the same acrylic material recommended for the DI technique . AnotherAll the results shown in our study were statistically significant on all three tested surfaces, but on the interproximal surface, the significance was weaker albeit acceptable . This caPrevious studies that compared the accuracy of different impression techniques used either digital scanning methods ,27 or anWhile promising, there remains the question that the digital impression technique may still not be accurate enough for full arch implant cases, such as the 6-implant full arch master model examined here ,29. OtheOur examination of the accuracy of the position of adjacent scan abutments revealed that the angles in area 6, which measures the two most distal abutments, were significantly different from those in the master model, for all study groups . The meaFramework design and fabrication as well as impression accuracy are important for framework fit, but standardized values for acceptance of passive fit are lacking. Marginal discrepancies of 30 up to 150 μm between frameworks and abutments have been suggested as acceptable to prevent biological and technical complications . HoweverAs mesenchymal stem cells were already being shown to accelerate osseointegration with dental implants, other novel therapeutic modalities could be beneficial for future researchers in relation to different impression techniques .Our results represent the first digital comparison of the three separate surfaces of a scan body in a master model of six vertically aligned analogs. The limitation of the current study was that it is an in vitro study, which cannot fully reproduce the clinical conditions. Other limitations are the small sample size and the use of only one implant company with parallel analogs. Different results of the impression accuracy may be obtained with the angulated placement of implants. More research is needed in order to verify our results on a model with tilted analogs, which more truthfully replicates the clinical situation. In addition, further in vivo research is required.Within the limits of this in vitro study, it is possible to conclude that the indirect closed tray snap on impression technique with unconnected plastic caps exhibited the same three-dimensional accuracies as the direct open tray technique. The indirect closed tray snap on impression technique with connected plastic caps was less accurate than either the indirect closed tray snap on impression technique with unconnected plastic caps or the direct open tray technique. In the case of full arch implant supported prostheses, inaccuracies may be expected in the most distal implants for all the three impression techniques evaluated in this study. More research needs to be performed in the future in order to verify our results on a model with a variety of implant positions: tilted analogs, different heights and different platforms which are more truthfully replicate the clinical situation.


In the United States (US), low-income workers are being pushed away from city centers where the cost of living is high. The effects of such changes on labor mobility and housing price have been explored in the literature. However, few studies have focused on the occupations and specific skills that identify the most susceptible workers. For example, it has become increasingly challenging to fill the service sector jobs in the San Francisco (SF) Bay Area because appropriately skilled workers cannot afford the growing cost of living within commuting distance. With this example in mind, how does a neighborhood's skill composition change as a result of higher housing prices? Are there certain skill sets that are being pushed to the geographical periphery of a city despite their essentialness to the city's economy? Our study focuses on the impact of housing prices with a granular view of skills compositions to answer the following question: Has the density of cognitive skill workers been increasing in a gentrified area? We hypothesize that, over time, low-skilled workers are pushed away from downtown or areas where high-skill establishments thrive. Our preliminary results show that high-level cognitive skills are getting closer to the city center indicating adaptation to the increase of median housing prices as opposed to low-level physical skills that got further away. We examined tracts that the literature indicates as gentrified areas and found a pattern in which there is a temporal increase in median housing prices and the number of business establishments coupled with an increase in the percentage of skilled cognitive workers. Alfred Marshall defined cluster theory in his book Principles of Economics as “concentration of specialized industries in particular localities” where industries tend to cluster to facilitate resources and human capital flows in cities  in neighborhoods happened with changes in the skill/job spatial composition in those areas? We hypothesize that, over time, low-skilled workers are pushed away from city centers or areas where highly skilled establishments thrive.Few studies have looked into the effect of increasing housing prices on workers' skills. Our contribution, in this paper, focuses on the impact of housing prices To answer the research questions, we augmented traditional census information  with additional detailed information about the skill sets in urban labor markets. While traditional approaches rely only on coarse demographic variables to explain economic growth, we utilized behavioral features  and detailed worker abilities  to study the effect of gentrification on neighborhoods' skill compositions. Our approach included integrating skills and job networks with various data sources at the census tract level over 17 years (2002–2018) for Dallas, LA, and SF. We used median housing prices and the number of business establishments as metrics of gentrification. We tested for changes in the average travel time and skill compositions of workers at neighborhood levels. Our method included testing spatial autocorrelations for skills and performance regressions to assess the relationship between median housing prices and changes in business establishments and skill compositions. All of the data used in our study are publicly available. Since cities, such as SF, LA, and Dallas have gone through major changes over the last two decades, we focus our study on analyzing them.Our study utilizes various data sources to examine gentrification from different perspectives  at the neighborhood level. A summary of the data used can be found in The Center for Economic Studies at the U.S. Census Bureau offers various data products and resources for public and research purposes, including Longitudinal Employer-Household Dynamics (LEHD)  is an online database that provides a detailed description of the U.S. labor market. It is created by job analysts and surveys to identify the skills, tasks, and technologies associated with an occupation in the US. It also provides information on the share of jobs associated with the 20 NAICS sectors. The database is updated regularly  Bureau,  is an anOur study analyzed each city at the geographical resolution of a census tract, which is equivalent to a neighborhood, and used annual temporal resolution (2002–2018). We explored the core-based statistical areas (CBSA) of Dallas-Fort Worth-Arlington, the SF Bay Area, and LA. The CBSA of Dallas has 1,312 tracts, with an average commuting flow of 539,758 pairs between tracts over 17 years, and SF has 1,620 tracts, with an average commuting flow of 759,139 workers. As for LA, we used CBSA boundaries with 3,925 tracts and an average commuting flow of 2,280,330. When addressing these various data sources, we needed to curate and integrate different datasets to aid our analysis. Therefore, we categorized our data curation and mining approach into three categories: skills, housing prices, and business establishments.*NET provided the percentage of employment for each occupation for the 20 NAICS sectors. With data from the SkillScape analysis  files provided the employment distribution of the 20 NAICS sectors, and OIn these two categories, we want to get the median housing prices and the number of business establishments for each tract. We used the Zillow dataset for median housing prices and CBP datasets for business establishments. These two datasets are only available for the zip code level, so to convert it to tract level, we used the Department of Housing and Urban Development - United States Postal Service (HUD-USPS) ZIP Code Crosswalk data. Using the crosswalk data, we were able to generate the median housing prices and the number of business establishments for each tract. Also, we used the Consumer Price Index . In our study, we tested for changes in the spatial autocorrelation of the cognitive fraction over time within tracts. We calculated both the Global Moran's index to obtain the overall trend of a city and the local Moran's index to see the patterns of hot spots  and cold spots  of the cognitive fraction within the cities. We used queen contiguity-based weights to define the spatial neighbors and the cognitive fraction as the variable to test its autocorrelation with these spatial weights.To capture the dynamic behavior of mobility flows, we used techniques from network science to understand how different income groups travel to work overtime. We constructed directed networks for the flows of low- and middle-high-income groups, where each source node represents a home tract and each target node represents a workplace tract. Nodes are connected by the number of workers commuting from home to work based on their income. Calculations of the temporal change of the network through weighted degree measures and centrality help assess flow networks. The weighted degree will provide information on where each income group is constructed in terms of the workplace and how they are shifting over time. We used the weighted eigenvector centrality of all nodes to understand the importance of a tract in commuting the various income groups.In order to examine the relationship between the different variables and the median housing prices over the years, we built a regression model that takes as input cognitive skill fraction, centrality, number of business establishments and produces median housing prices for each census tract.Network visualizations show the dynamics of how different income groups commute to workplaces that we defined as the city's downtown and Silicon Valley for the Bay Area for the years of 2002 and 2018. We use weighted out-degree networks to capture the changes in the home place of high- and low-income workers. SF Bay area clearly shows the difference in flows between the two groups in For our first question of how spatial composition changed in neighborhoods over the period of 17 years, we assess this by looking into the global spatial autocorrelation (Moran's I) of the cognitive fraction. In particular, to examine if the cognitive skill workers tend to live near each other or not on a temporal level. The results shown in Local indicator of spatial association will identify the significant locations of hot spots and cold spots. Specifically, high values of positive autocorrelation are clustered, and the low values of negative autocorrelation are clustered. The significance LISA maps of the SF Bay Area in 2 = 0.177). Also, we consider the number of business establishments in model 3 (R2 = 0.035). Models 4–6 demonstrate that cognitive skill fraction contributes the most between the first three variables. In model 7, we consider variables for the cities. Modeling with these geographical variables alone performs worse than using cognitive (R2 = 0.16). Model 8 shows that the time variable almost does not contribute to the dependent variable (R2 = 0.002). Model 9 demonstrates the improved performance from including the variable for centrality and establishments (R2 = 0.203), but maximum performance is achieved when including cognition as well (model 10 has R2 = 0.299). The standard errors and statistical significance of coefficient estimates are reported in the regression table. In summary, we find that the cognitive skill fraction (cognitive) explains the housing prices better than models using centrality, business establishment, city, or time alone.As we find out that cognitive skills cluster in highly gentrified areas, we wanted to test if cognitive skills contribute to housing prices. So, we compared it with another variable that could contribute to the housing prices by comparing different regression models in The main novelty of the paper is adding the lens of skills to explore the economic transformation affecting cities and neighborhoods. Other studies have used other proxies to skills, such as income and education. In our work, we used exact skills to quantify the skills changes for each neighborhood. In addition, this study quantifies the spatial impact of skills on commute patterns of middle-high- and low-income groups. We found that low-skill physical workers are being pushed out of the city center, which could eventually hurt the local economy. The work is a building block toward a granular view of specific skills changes at the neighborhood level and further examining their relation to gentrification. This was possible by combining and integrating various data from mobility networks to skills data. The LISA significance maps show how high values of cognitive skill workers have significantly clustered around the city center over time, pushing low values further for both SF and Dallas. However, this trend was not present in LA as it seems to be clustered in wealthy neighborhoods.Moreover, the global spatial correlation index for the distribution of cognitive fraction has increased between 2002 and 2018 for all areas of study, showing that an apparent change has forced this increase in global correlation. In addition, the flow networks show the difference in commuting patterns between the middle-high- and low-income groups. Furthermore, the regression experiment showed that the cognitive fraction contributed significantly to the median housing prices. This analysis can be done for all U.S. states. The change in cognitive fraction could identify areas to be gentrified and find opportunity zones for investment and future technology hubs to flourish the local economy. To compare between the three cities, we found that LA had the most remarkable average percentage change in cognitive fraction with an average percent increase of 6%, followed by Bay area with a percent increase of 5%, and Dallas with the lowest average percentage change of 3%. However, Dallas had the most significant spatial correlation with a 47% percentage increase in global Moran's I. In contrast, the other regions had a percentage change of 8 and 13% for Bay Area and LA, respectively.Our work is aligned with the perspective article titled “Toward understanding the impact of artificial intelligence on labor” (Frank et al., The original contributions presented in the study are included in the article/All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This study develops a novel framework of heterogeneous producer attitudes towards risk to analyze different, stated and revealed, roles of crop insurance premium subsidies and underlying policy objectives of the government. The analysis reveals a strong connection and a complementarity between the roles of premium subsidies in increasing producer participation in crop insurance, inducing a desired separating equilibrium in the presence of asymmetric information, and transferring income to agricultural producers participating in the program. Developing an alternative design of premium subsidies that can achieve the stated government objective of increased producer participation and induce any desired separating equilibrium at significantly reduced costs, our study rejects the idea that the income redistribution taking place under the current policy design is necessary for increasing producer participation in crop insurance. Indeed, the current policy design reveals that premium subsidies are either a means of income redistribution or a policy failure. The U.S. federal crop insurance is a major farm policy aimed at providing risk protection/reduced risk exposure to agricultural producers , 2. A keGiven the significant producer heterogeneity with respect to attitudes towards risk –21 and tThe objective of this study is to analyze and evaluate all different policy objectives/roles of premium subsidies and improve our understanding of the relationship between the stated and revealed government objectives and the role of premium subsidies in achieving these objectives.To study the role of premium subsidies in crop insurance policy design and implementation, our study develops a novel framework of analysis that explicitly accounts for the empirically relevant heterogeneity in producer attitudes towards risk and the multiple insurance options/contracts available to them. The explicit consideration of heterogeneous producer risk preferences is important in understanding the partial producer participation in crop insurance, differences in producer choices regarding insurance coverage as well as the asymmetric effects of the policy on producers with different risk preferences.The analysis reveals a strong connection and a complementarity between the stated and revealed policy objectives of the government. Using insights from our model, we identify an alternative design of premium subsidies that can achieve the stated government objective of increased producer participation and induce any desired separating equilibrium at reduced costs. The existence of such a mechanism rejects the idea that the income redistribution taking place under the current policy design is necessary for increasing producer participation in crop insurance.Overall, our manuscript makes three contributions to the literature. First, it introduces a novel framework of analysis that effectively captures the empirically relevant heterogeneity in producer attitudes towards risk (which has been ignored by the relevant literature) as well as the tradeoffs involved in producer insurance decisions in a parsimonious manner. Second, it develops and proposes an alternative design of the crop insurance policy mechanism that can increase producer participation  and induce any separating equilibrium at significantly lower costs. Third, by developing this new policy design, the analysis reveals that the premium subsidies in the current policy design are either a means of income redistribution or a policy failure.The rest of this manuscript is organized as follows. The next section provides some background information on the importance of premium subsidies in the evolution of crop insurance. Next, we introduce the theoretical framework of heterogeneous producer attitudes towards risk and analyze the producer decisions and welfare under the crop insurance policy. We then discuss the different roles of the premium subsidies in crop insurance, and present a policy design that can achieve increased producer participation and any desired separating equilibrium at reduced taxpayer costs. The final section summarizes and concludes the study.The inception of the Federal Crop Insurance Program dates back to 1938, when it was initiated as a risk protection mechanism following the dust bowl and unsuccessful attempts by the private industry to provide insurance to agricultural producers . Crop inSubsequent legislative reforms focusing on the structure and magnitude of premium subsidies further increased the size and scope of the program that ended up providing nationwide multi-peril crop insurance coverage for almost all available crops and commodities. Most notable among those reforms are the Federal Crop Insurance Reform Act of 1994 that increased premium subsidies to enhance producer participation in the program , 24, theDue to differences in their attitudes towards risk and level of risk aversion, agricultural producers differ in the costs they incur for being involved in a risky endeavor like agricultural production. The greater a producer’s aversion to risk, the greater the perceived costs of operating/producing under a given level of risk exposure, and the lower the expected net returns to production . To reduTo capture these elements, consider a continuum of agricultural producers differing in the level of their aversion to risk that have the choice between self-insuring, purchasing a low-coverage insurance policy, and purchasing a high-coverage policy. Note that, in reality, there are multiple insurance policies with different levels of risk coverage available to producers. While our model can be easily adapted to consider a large number of crop insurance contracts, such consideration would complicate the analysis without affecting the qualitative nature of our results.A ∈ [0.1] be the attribute that differentiates producers with greater values of A corresponding to greater aversion to risk. The expected net returns associated with the different options for the producer with differentiating attribute A are given by:ERsi, ERl and ERh are the expected net returns from agricultural production under self-insurance, low-coverage crop insurance and high-coverage crop insurance, respectively; ERP are the expected returns to agricultural production that are common across producers; wl and wh are the costs of low-coverage and high-coverage crop insurance, respectively, with wh > wl and β, γ and δ are risk exposure parameters capturing the producer risk exposure under self-insurance, low-coverage crop insurance and high-coverage crop insurance, respectively. The ERP are given by (p-c)q where p is the farm price of the agricultural product, c is the cost of producing this product, and q is the quantity produced. Depending on the source of uncertainty , the parameters p, c and q would represent the expected price, expected cost and expected output, respectively. As pointed out by an anonymous reviewer, the expected returns to production could vary among the different insurance options if, due to moral hazard, the procurement of insurance affected producers’ effort and production decisions. While consideration of differences in the expected returns to production would complicate the analysis, it would not affect the results of our study.Let β > γ > δ. In this context, βA, γA and δA represent the costs associated with (risky) agricultural production under the different insurance options for the producer with differentiating attribute A. The greater the riskiness of agricultural production/producer exposure to risk and/or the greater the producer aversion to risk, the greater the producer costs of being involved in this risky endeavor.To capture the reduction in risk exposure due to insurance coverage, we assume that ERsi, ERl and ERh for the empirically relevant case where the different insurance options enjoy positive shares of the market.The producer insurance decision depends on the relative expected net returns associated with self-insurance, low-coverage crop insurance and high-coverage crop insurance. The producer with risk aversionA ∈[0.Al)) prefer to self-insure, producers with intermediate levels of risk aversion A ∈  prefer the low-coverage crop-insurance, while more risk averse producers with A ∈  are given by:Before concluding this section, it is important to note that, in the spirit of , our simsl and sh are the government determined premium subsidies for low- and high-coverage crop insurance, respectively. These subsidies are proportional to the insurance costs/premiums wl and wh taking, therefore, values between 0 and 1, and decline as coverage levels increase . The greater is the value of a premium subsidy, the lower the costs of the specific crop insurance coverage contract, and the greater the expected net returns associated with this insurance contract, i.e., As noted earlier, an important component of the crop insurance policy are the premium subsidies for the different crop insurance contract options. These premium subsidies are designed to reduce the insurance costs to producers and, in their presence, the producer expected net returns function becomes:All other variables are as defined previously. As shown in Result 1: The introduction of crop insurance premium subsidies increases producer participation in the policy, which is the stated goal of the government.Crop insurance data from the Risk Management Agency (RMA), available in The provision of multiple crop insurance contract options to agricultural producers reveals the government’s desire to have different producers/producers with different attitudes towards risk choose different insurance coverage contracts. Obviously, if this were not the case, i.e., if the government wanted all producers to choose the same insurance coverage, it could/would have, simply, made one crop insurance coverage option available to producers. Put in a different way, the provision of multiple insurance coverage contracts reveals the government’s desire for the existence of a separating equilibrium where producers with different levels of risk aversion choose different insurance contracts.With the producer attitudes towards risk/level of risk aversion being private information, this represents a typical case of asymmetric information where the type of the agent/informed party is hidden to the principal/uniformed party. In such a case, the provision of a menu of contracts is part of the appropriate response of the uninformed party (government in our case) that desires to resolve the information asymmetry and have different agents/producers choose the contract designed for them. Subsidies linked to the different contracts  can then be used to satisfy incentive compatibility and induce different producer groups choose the policies designed for them .In the context of our study, the provision of low- and high-coverage insurance policies reveals the government’s desire to have producers with intermediate and high aversion to risk choose low- and high-coverage crop insurance contract, respectively, with the premium subsidies helping determine the desirable threshold levels of risk aversion  and the share of producers under each insurance contract.sl. If the government is interested in maintaining/achieving a certain share of producers in the high-coverage option, then it has to also subsidize the high-coverage policy. Note that, twenty years after the introduction of 80% and 85% coverage levels in 1999, high-coverage policies grew to represent 26% of insured acres and 32% of premium subsidies.In the context of the analysis in the previous section, for instance, in addition to increasing producer participation in crop insurance, subsidizing the low-coverage insurance policy also changes the share of producers that purchase a high-coverage crop insurance contract as a number of them find it optimal to switch to the low-coverage policy in the presence of xl and xh in sl and sh, the government can achieve this (and any other) change in the shares  of producers choosing the different insurance coverage contracts, as those shares are, indeed, functions of the relative subsidies received by the two contracts, i.e.,slwl is less than shwh inducing an increased number of producers to opt for the high-coverage crop insurance contract, the premium subsidies can be structured such that the share of producers opting for the high-coverage insurance contract is reduced or stays the same. For instance, while ARPA resulted in a regressive proportional scheme of the premium subsidy rates , the dollar amount of the premium subsidy can still increase with the coverage level , as the difference in the subsidy rates can be outweighed by the difference in the insurance premiums wh and wl [slwl exceeds shwh and producers who initially had a high-coverage insurance contract  was $4.74, while the average subsidy for high-coverage insurance  was $2.49 per acre [slwl and shwh, and are asymmetric across the different policy participants. Specifically, when slwl is less than shwh .As noted earlier, the stated role of premium subsidies is to increase producer participation in crop insurance. As our analysis has shown, however, if increased producer participation were the only goal of the government, it could have been achieved much more efficiently by providing subsidies to low-coverage insurance policies only . Such a policy design would have still attracted the desired producer group to participate in crop insurance and would have avoided the income transfer to existing high-coverage insurance buyers. Based on Result 2, however, one could argue that the provision of subsidies to both low- and high-coverage insurance contracts is not evidence of a government desire to transfer income to more risk averse producers but that it reveals, instead, a desire to induce a certain separating equilibrium , the introduction of the premium subsidies does result in income transfers from taxpayers to policy participants, the question that naturally arises (and is at the heart of this research) is whether these transfers are a goal or a necessity for the desired increased participation (and a separating equilibrium) to emerge. To answer this question, we need to evaluate whether the government could achieve the desired increased participation and any separating equilibrium at reduced costs. It turns out that it can, which makes income redistribution very much a goal of this government policy.sl to new participants only. Without a subsidy paid to producers with low-coverage insurance already in the program, there would be no need for a subsidy for existing producers with high-coverage insurance to maintain the desired separating equilibrium (and the share/type of producers opting for high-coverage crop insurance). In particular, the government could have achieved the desired increase in producer participation by providing the premium subsidy Result 4: Providing premium subsidies only to new policy participants can increase the efficiency of the policy in increasing producer participation in crop insurance and inducing a desired separating equilibrium.At this point, it is important to reiterate that, while our analysis focuses on the introduction of new premium subsidies, our results are more general and apply also to cases where the government increases the magnitude of existing subsidies. In such a case, under our proposed mechanism, it is the increase in the premium subsidy associated with the low-coverage insurance that would be available only to new policy participants . Put in a different way, in cases where the goverenment already subsidizes different insurance coverage policies, our proposed mechanism would not remove existing subsidies from current policy participants but would, instead, make the increase in the current premium subsidies available only to new policy participants.To assess the magnitude of the savings associated with the implementation of our proposed policy design, we compare its costs to those of ARPA, focusing on the years before and after the implementation of this reform. RMA data indicates that ARPA increased producer acreage enrollment from 206.4 million acres in 2000 to 211.3 million acres in 2001 . With thsh to existing policy participants. Since sl to existing policy participants would be zero under this mechanism, the amount of sh that would be needed for the desired adjustment to occur would be smaller than that under the current policy design. The reason is that, as shown earlier, it is the difference between the subsidies to low- and high-coverage policies that determines the shares of producers opting for the different policies. Reducing one of them to zero (as the current participants are not subsidized under this mechanism) reduces also the size of the other subsidy that is required for the desired adjustment to occur.It is important to note that, in addition to being very efficient, this policy design is also very flexible. For instance, if an increase in the share of producers purchasing high-coverage policy were desired, it could be easily achieved by providing The fact that the government could have achieved its objectives of increasing producer participation and inducing a desired separating equilibrium by subsidizing only new policy participants but chose to provide subsidies to all policy participants (both new and existing ones), reveals either that income redistribution through crop insurance is very much an objective of the government or that the current policy design constitutes a policy failure.Result 5: Income transfers from taxpayers to agricultural producers are an objective of the crop insurance policy and not a necessary cost of increasing producer participation and inducing a desired separating equilibrium.This paper develops a model of heterogeneous producer attitudes towards risk to analyze different, stated and revealed, roles of crop insurance premium subsidies. The stated government objective of premium subsidies to increase producer participation in crop insurance is evaluated along with their role in inducing the desired producer behavior and a separating equilibrium in the presence of asymmetric information, and transferring income from taxpayers to agricultural producers/policy participants.The analysis reveals a strong connection and a complementarity between the stated and revealed policy objectives of the government. Premium subsidies can, indeed, increase producer participation in the program, induce a (any) desired separating equilibrium with producers with different levels of risk aversion choosing different levels of risk coverage, and result in welfare transfers to agricultural producers.The study then tests the assertion that the income transfers occurring through premium subsidies are a necessary cost for increasing producer participation in the program. To do so, we develop an alternative design of premium subsidies, one in which increased participation occurs through the provision of subsidies to new policy participants only. The proposed design can achieve the stated government objective of increased producer participation at reduced costs and rejects the idea that the income redistribution taking place under the current policy design is necessary for increasing producer participation in crop insurance.In fact, the proposed alternative policy design can also be modified to induce any desired separating equilibrium, also at reduced costs. The presence of a policy design that can achieve increased producer participation and induce any desired separating equilibrium at reduced costs reveals that the premium subsidies in the current policy design are either a means of income redistribution or a policy failure.S1 Data(XLS)Click here for additional data file.