Attenuation Methods Research Articles

Application of the local maximum synchrosqueezing transform for seismic data

Seismic signal analysis is the main step in data processing through the petroleum exploration via costly seismic investigations. Precision of target delineation by seismic data for exploratory drilling strongly depends on resolution of the seismic image. However, resolution of the seismic image is restricted by the band-limited nature of the seismic signal and inherent deficiencies in signal enhancement and random noise attenuation methods. Generally, it is required to increase resolution of the seismic data both in time and frequency domains. General solution to achieve this goal is employing time – frequency transformation (TFT) methods. The most applicable and conventional TFT method is the short time Fourier transform (STFT). Nevertheless, the STFT method does not provide sufficient resolution for further seismological interpretation on data. Thus, reassignment and simultaneous synchrosqueezing transform methods were introduced that increase resolution in time by reassignment of coefficients to their true position. However, they are still not appropriate for obtaining required resolution in seismic signal. The local maximum synchrosqueezing transform (LMSST) was introduced as an efficient method for signal analysis. The LMSST method yet was not used for analysis of seismic data and the procedure of its parameters optimization for applying on seismic data is unclear. Therefore, in the presented study, we propose a strategy for defining optimum parameters of the LMSST method and the procedure of its application on seismic data, where high resolution seismic image is required for hydrocarbon exploration. The proposed strategy was applied on two synthetic data examples, considering the quality factor expression and contamination by random noise and a field data example from a natural gas reservoir. Result of applying the proposed strategy on synthetic and field data examples and comparison of results with the leading-edge methods, revealed that this strategy could be considered as an alternative to the common signal enhancement methods. Additionally, the proposed method consists of the advantage of easy implementation and full reconstruction of the original signal. It was also proved that the proposed strategy is a robust method against added random noise compared to other competitive methods when applied on nonstationary seismic signal.

Changes in circulating lymphocytes and lymphoid tissue associated with vaccination of colostrum deprived calves

The objective of this study was to compare immunological responses and lymphoid depletion in young, colostrum deprived calves following administration of vaccines containing modified-live bovine viral diarrhea virus (BVDV). A group of calves exposed to a typical virulence non-cytopathic (ncp) BVDV-2 field strain (ncp exposed) was included to compare responses of calves receiving vaccine to responses generated against a field strain (mimicking a natural infection). A negative control group administered a placebo was used in all comparisons. All vaccines used in the study were administered per manufacturer recommendations while ncp BVDV exposed calves received 5 ml intranasally (2.5 ml/nare; 4.2 × 106 TCID50/ml) of the BVDV-2 field strain. Samples collected at each time point included nasal swabs for virus detection, blood samples for complete blood counts and detection of viremia, PBMCs for flow cytometric analysis, serum for virus neutralization titers, and thymus tissue at necropsy for evaluation of lymphoid depletion. A measurable neutralizing BVDV titer was observed for all treatment groups excluding the control animals, which remained negative during the study period. Virus shedding was only detected from the ncp vaccinated and ncp exposed calves. A decline from baseline was observed for peripheral lymphocyte and CD4+ cells for the groups receiving the adjuvanted cytopathic (cp) vaccine, the double deleted genetically modified (ddGM) vaccine, the ncp vaccine and ncp exposed calves, but not for the control group or groups receiving cp vaccines. Thymus depletion was observed for the ncp vaccine and ncp exposed calves and to a lesser extent for the ddGM vaccine calves. Collectively, these data suggest that the virus biotype, method of attenuation, presentation, and use of adjuvant will influence vaccine impacts on lymphoid tissues and the immune response. As such, multiple variables should be considered when determining costs and benefits of vaccination.

Two‐dimensional dictionary learning for suppressing random seismic noise

ABSTRACTDictionary learning is a successful method for random seismic noise attenuation that has been proven by some scholars. Dictionary learning–based techniques aim to learn a set of common bases called dictionaries from given noised seismic data. Then, the denoising process will be performed by assuming a sparse representation on each small local patch of the seismic data over the learned dictionary. The local patches that are extracted from the seismic section are essentially two‐dimensional matrices. However, for the sake of simplicity, almost all of the existing dictionary learning methods just convert each two‐dimensional patch into a one‐dimensional vector. In doing this, the geometric structure information of the raw data will be revealed, leading to low capability in the reconstruction of seismic structures, such as faults and dip events. In this paper, we propose a two‐dimensional dictionary learning method for the seismic denoising problem. Unlike other dictionary learning–based methods, the proposed method represents the two‐dimensional patches directly to avoid the conversion process, and thus reserves the important structure information for a better reconstruction. Our method first learns a two‐dimensional dictionary from the noisy seismic patches. Then, we use the two‐dimensional dictionary to sparsely represent all of the noisy two‐dimensional patches to obtain clean patches. Finally, the clean patches are patched back to generate a denoised seismic section. The proposed method is compared with the other three denoising methods, including FX‐decon, curvelet and one‐dimensional learning method. The results demonstrate that our method has better denoising performance in terms of signal‐to‐noise ratio, fault and amplitude preservation.

Attenuation Methods for Live Vaccines.

Vaccination was developed by Edward Jenner in 1796. Since then, vaccination and vaccine development research has been a hotspot of research in the scientific community. Various ways of vaccine development are successfully employed in mass production of vaccines. One of the most successful ways to generate vaccines is the method of virulence attenuation in pathogens. The attenuated strains of viruses, bacteria, and parasites are used as vaccines which elicit robust immune response and confers protection against virulent pathogens. This chapter brings together the most common and efficient ways of generating live attenuated vaccine strains in viruses, bacteria, and parasites.

Transmission loss of plates with multiple embedded acoustic black holes using statistical modal energy distribution analysis

Acoustic black holes (ABHs) in beams and plates have been extensively studied as a passive method for vibration attenuation and noise reduction. However, most research to date has focused on analyzing the behavior of a single ABH structural element, using numerical or semi-analytical deterministic approaches. If ABHs are to be exploited for practical industrial applications, there is a need to characterize their performance in complex built-up structures and to describe them with statistical methods in the mid-high frequency range. This paper presents a first step towards this goal by employing statistical modal energy distribution analysis (SmEdA) to evaluate the transmission loss of ABH panels separating two air cavities. SmEdA splits vibroacoustic systems into subsystems and establishes power balance equations between the modes belonging to different subsystems. This avoids the energy equipartition assumption of traditional statistical energy analysis (SEA) and extends it to low modal overlap systems. In this work, the benefits of embedding ABHs on plates for noise reduction between cavities are predicted with SmEdA. The role played by the size, shape and number of ABH indentations on the plate are inspected, as well as the influence of other parameters like the truncation thickness, ABH order and damping. The effects of added mass and stiffness of the damping layer are investigated and it is observed that, with proper design, ABH plates can exhibit substantial transmission loss improvement in the vicinity of the critical frequency of uniform plates. Both resonant and non-resonant transmission are considered in the analysis.

Investigation of Recombination Parameters of Nonequilibrium Charge Carriers in Si Technological Plates by Thermal Imaging Method

The research approach on the investigation of recombination parameters of nonequilibrium charge carriers in Si technological plates by thermal imaging method is offered in this paper. The lifetime, diffusion length and surface recombination velocity of charge carriers are taken into account. The method is based on a study of the spatial distribution of Si samples thermal radiation beyond the self-absorption edge in the spectral range of 3–5 μm using by an IR camera. There are experimental results of silicon technological samples researches: distribution of the excess charge carriers concentration in silicon samples (n-Si, ρ = 500 Ω⋅cm, d = 8 mm) and the diffusion distribution of charge carriers at T = 150 °C. Temperature dependence of the diffusion length and volumetric lifetime in silicon samples is measured by three different methods: using an IR camera, by the kinetics of thermal radiation decline beyond the self-absorption edge during laser excitation, and by the method of photoconductivity attenuation. This approach is implemented in the process of input control of silicon plates used for solar panels manufacture at JSC “Quasar.”

Nonstationary signal inversion based on shaping regularization for random noise attenuation

Prediction filtering is one of the most commonly used random noise attenuation methods in the industry; however, it has two drawbacks. First, it assumes that the seismic signals are piecewise stationary and linear. However, the seismic signal exhibits nonstationary due to the complexity of the underground structure. Second, the method predicts noise from seismic data by convolving with a prediction error filter (PEF), which applies inconsistent noise models before and after denoising. Therefore, the assumptions and model inconsistencies weaken conventional prediction filtering’s performance in noise attenuation and signal preservation. In this paper, we propose a nonstationary signal inversion based on shaping regularization for random noise attenuation. The main idea of the method is to use the nonstationary prediction operator (NPO) to describe the complex structure and obtain seismic signals using nonstationary signal inversion instead of convolution. Different from the convolutional predicting filtering, the proposed method uses NPO as the regularization constraint to directly invert the effective signal from the noisy seismic data. The NPO varies in time and space, enabling the inversion system to describe complex (nonstationary and nonlinear) underground geological structures in detail. Processing synthetic and field data results demonstrate that the method effectively suppresses random noise and preserves seismic reflection signals for nonstationary seismic data.

Temperature Sensitivity: A Potential Method for the Generation of Vaccines against the Avian Coronavirus Infectious Bronchitis Virus.

The Gammacoronavirus infectious bronchitis virus (IBV) is a highly contagious economically important respiratory pathogen of domestic fowl. Reverse genetics allows for the molecular study of pathogenic determinants to enable rational vaccine design. The recombinant IBV (rIBV) Beau-R, a molecular clone of the apathogenic Beaudette strain, has previously been investigated as a vaccine platform. To determine tissues in which Beau-R could effectively deliver antigenic genes, an in vivo study in chickens, the natural host, was used to compare the pattern of viral dissemination of Beau-R to the pathogenic strain M41-CK. Replication of Beau-R was found to be restricted to soft tissue within the beak, whereas M41-CK was detected in beak tissue, trachea and eyelid up to seven days post infection. In vitro assays further identified that, unlike M41-CK, Beau-R could not replicate at 41 °C, the core body temperature of a chicken, but is able to replicate a 37 °C, a temperature relatable to the very upper respiratory tract. Using a panel of rIBVs with defined mutations in the structural and accessory genes, viral replication at permissive and non-permissive temperatures was investigated, identifying that the Beau-R replicase gene was a determinant of temperature sensitivity and that sub-genomic mRNA synthesis had been affected. The identification of temperature sensitive allelic lesions within the Beau-R replicase gene opens up the possibility of using this method of attenuation in other IBV strains for future vaccine development as well as a method to investigate the functions of the IBV replicase proteins.

Canine intrahepatic portosystemic shunt insertion into the systemic circulation is commonly through primary hepatic veins as assessed with CT angiography.

Congenital intrahepatic portosystemic shunts (IHPSS) in dogs are traditionally classified as right, left, or central divisional. There are few descriptive studies regarding the variation of IHPSS within these categories. This multicenter, analytical, cross-sectional study aimed to describe a large series of dogs with CT angiography (CTA) of IHPSS, hypothesizing that there would be variation to the existing classification. Ninety CTA studies were assessed for IHPSS type, insertion, and the relationship of the insertion to the primary hepatic veins. Ninety-two percent of IHPSS inserted into a primary hepatic vein (HV) or phrenic vein, 8% inserted directly into the ventral aspect of the intrahepatic caudal vena cava. The most common IHPSS type was a single right divisional (44%), including those inserting via the right lateral HV or the caudate HV. Left divisional IHPSS (33%) inserted into the left HV or left phrenic vein. Central divisional IHPSS (13%) inserted into the quadrate HV, central HV, dorsal right medial HV, or directly into the ventral aspect of the intrahepatic caudal vena cava. Multiple sites of insertion were seen in 9% of dogs. Within left, central, and right divisional types, further subclassifications can therefore commonly be defined based on the hepatic veins with which the shunting vessel communicates. Relating IHPSS morphology to the receiving primary HV could make IHPSS categorization more consistent and may influence the type and method of IHPSS attenuation recommended.

A Novel Boat Shock Vibration Control using Momentum Exchange Principle with Pre-Straining Spring Mechanism

This research proposes a new method for boat impact vibration attenuation using the exchange of momentum principle with a pre-straining spring mechanism. The boat dynamic is modeled using a hinged-supported beam structure. The wave excitation on the boat hull is expressed using one degree of freedom spring-mass system. The simulation study is performed to evaluate the impact damper performance in reducing the boat shock response. Two kinds of momentum exchange impact damper i.e., without and with pre-straining spring mechanism, are evaluated. The simulation results show that the impact damper with pre-straining spring mechanism (PSMEID) is better than the passive momentum exchange impact damper (PMEID) in reducing the boat shock vibration response

Amplification of Vibrations in High-Speed Railway Embankments by Passive Ground Vibration Barriers

The objective of the present study is to characterise the dynamic response of ballasted railway embankments subject to high-speed train loads, for the track conditions with and without inclusions of geofoam in-filled trenches next to the embankments for passive isolation of ground vibrations. Full-scale models of the ballasted railway track sections were developed for the simulation of high-speed train transit. Although vibration isolation trenches have been characterised as a suitable method for attenuation of ground-borne railway vibrations propagating away from the track, the results from the present study signify that the embankments supporting the railway track are subject to augmented levels of vibrations, due to reflection of ground vibrations from the soil–trench interface back into the embankment. In-filling of trenches with EPS (expanded polystyrene) geofoam of high buffer stiffness results in stronger reflection of ground vibrations back into the railway embankment. Augmented levels of track vibration are also estimated, when geofoam with higher densities are used for in-filling the trench. Deployment of vibration isolation trenches with higher depths result in stronger reflection of ground vibrations as well, especially when the trench is deployed at locations farther from the track. In general, amplification of vibrations in the railway embankment is higher when the trains transit at faster speeds. Reflection of vibrations by the passive vibration isolation trenches is inevitable, and hence, it is recommended that rail pads or under-sleeper pads shall be used in conjunction with the passive trenches for limiting the amplification of vibrations in the embankment.

Structure-Oriented DTGV Regularization for Random Noise Attenuation in Seismic Data

Noise attenuation is a very important step in seismic data processing, which facilitates accurate geologic interpretation. Random noise is one of the main factors that lead to reductions in the signal-to-noise ratio (SNR) of seismic data. It is necessary for seismic data, including complex geological structures, to develop a number of new noise attenuation technologies. In this article, we concern with a new variational regularization method for random noise attenuation of seismic data. Considering that seismic reflection events often have spatially varying directions, we first employ the gradient structure tensor (GST) to estimate the spatially varying dips point by point and propose the structure-oriented directional total generalized variation (DTGV) (SODTGV) functional. Then, we employ the SODTGV as a regularizer to establish an ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -SODTGV model and develop the primal-dual algorithm for solving this model. Next, the choice of the model parameters is discussed. Finally, the proposed model is applied to restore noisy synthetic and field data to verify the effectiveness of the proposed workflow. For contrastive methods, we select the structure adaptive median filtering (SAMF), anisotropic total variation (ATV), total generalized variation (TGV), DTGV, median filtering, KL transform, SVD transform, and curvelet transform. The synthetic and real seismic data examples indicate that our proposed method can preferably improve the vertical resolution of seismic profiles, enhance the lateral continuity of reflection events, and preserve local geologic features while improving the SNR. Moreover, the proposed regularization method can also be applied to other inverse problems, such as image processing, medical imaging, and remote sensing.

Identification of Water Hammering for Centrifugal Pump Drive Systems

Water hammering is a significant problem in pumping systems. It damages the pipelines of the pump drastically and needs to identify with an intelligent method. Various conventional methods such as the method of characteristics and wave attenuation methods are available to identify water hammering problems, and the predictive control method is one of the finest and time-saving methods that can identify the anomalies in the system at an early stage such that the device can be saved from total damage and reduce energy loss. In this research, a machine learning (ML) algorithm has used for a predictive control method for the identification of water hammering problems in a pumping system with the help of simulations and experimental-based works. A linear regression algorithm has been used in this work to predict water hammering problems. The efficiency of the algorithm is almost 90% compared to other ML algorithms. Through a Vib Sensor app-based device at different pressures and flow rates, the velocity of the pumping system, a fluctuation between healthy and faulty conditions, and acceleration value at different times have been collected for experimental analysis. A fault created to analyze a water hammering problem in a pumping system by the sudden closing and opening of the valve. When the valve suddenly closed, the kinetic energy in the system changed to elastic resilience, which created a series of positive and negative wave vibrations in the pipe. The present work concentrates on the water hammering problem of centrifugal pumping AC drive systems. The problem is mainly a pressure surge that occurs in the fluid, due to sudden or forced stops of valves or changes in the direction and momentum of the fluid. Various experimental results based on ML tool and fast Fourier transformation (FFT) analysis are obtained with a Vib Sensor testbed set-up to prove that linear regression analysis is the less time-consuming algorithm for fault detection, irrespective of data size.

Disturbance Attenuation with Minimization of Ellipsoids Restricting Phase Trajectories in Transition and Steady State

Abstract A new method for attenuation of external unknown bounded disturbances in linear dynamical systems with known parameters is proposed. In contrast to the well known results, the developed static control law ensures that the phase trajectories of the system are located in an ellipsoid, which is close enough to the ball in which the initial conditions are located, as well as provides the best control accuracy in the steady state. To solve the problem, the method of Lyapunov functions and the technique of linear matrix inequalities are used. The linear matrix inequalities allow one to find optimal controller. In addition to the solvability of linear matrix inequalities, a matrix search scheme is proposed that provides the smallest ellipsoid in transition mode and steady state with a small error. The proposed control scheme extends to control linear systems under conditions of large disturbances, for the attenuation of which the integral control law is used. Comparative examples of the proposed method and the method of invariant ellipsoids are given. It is shown that under certain conditions the phase trajectories of a closed-loop system obtained on the basis of the invariant ellipsoid method are close to the boundaries of the smallest ellipsoid for the transition mode, while the obtained control law guarantees the convergence of phase trajectories to the smallest ellipsoid in the steady state.

Multiple attenuation with 3D high-order high-resolution parabolic Radon transform using lower frequency constraints

The parabolic Radon transform is one of the most commonly used multiple attenuation methods in seismic data processing. The 2D Radon transform cannot consider the azimuth effect on seismic data when processing 3D common-depth point gathers; hence, the result of applying this transform is unreliable. Therefore, the 3D Radon transform should be applied. The theory of the 3D Radon transform is first introduced. To address sparse sampling in the crossline direction, a lower frequency constraint is introduced to reduce spatial aliasing and improve the resolution of the Radon transform. An orthogonal polynomial transform, which can fit the amplitude variations in different parabolic directions, is combined with the dealiased 3D high-resolution Radon transform to account for the amplitude variations with offset of seismic data. A multiple model can be estimated with superior accuracy, and improved results can be achieved. Synthetic and real data examples indicate that even though our method comes at a higher computational cost than existing techniques, the developed approach provides better attenuation of multiples for 3D seismic data with amplitude variations.

Prognostic factors for short-term survival of dogs that experience postattenuation seizures after surgical correction of single congenital extrahepatic portosystemic shunts: 93 cases (2005-2018).

To identify prognostic factors for short-term survival of dogs that experience seizures within 7 days after surgical correction of single congenital extrahepatic portosystemic shunts (cEHPSS). Multi-institutional retrospective study. Ninety-three client-owned dogs. Medical records at 14 veterinary institutions were reviewed to identify dogs that underwent surgical attenuation of a single cEHPSS from January 1, 2005 through February 28, 2018 and experienced postattenuation seizures (PAS) within 7 days postoperatively. Logistic regression analysis was performed to identify factors associated with 1-month survival. Factors investigated included participating institution, signalment, shunt morphology, concurrent/historical conditions, presence of preoperative neurologic signs, presence of preoperative seizures, aspects of preoperative medical management, surgical details including method and degree of shunt attenuation, type of PAS (focal only or generalized ± focal), drugs administered as part of the treatment of PAS, and development of complications during treatment of PAS. Thirty (32.3%) dogs survived to 30 days. Seventy-six (81.7%) dogs experienced generalized PAS. Factors positively associated with short-term survival included having a history of preoperative seizures (P = .004) and development of focal PAS only (P = .0003). Most nonsurvivors were humanely euthanized because of uncontrolled or recurrent seizures. Dogs that experienced PAS that had a history of preoperative seizures and those that experienced focal PAS only had significantly improved short-term survival. The results of this study provide information that will help in the counseling of owners who seek treatment for PAS after surgical correction of cEHPSS. © 2020 The American College of Veterinary Surgeons.

Seismic Interference Noise Attenuation by Convolutional Neural Network Based on Training Data Generation

External source interference noise (ESIN) is a common kind of noise in marine seismic data acquisition. According to the noise-to-signal ratio (NSR), a shot gather can be divided into a low NSR part and a high NSR part. The existing ESIN attenuation methods work well in high NSR parts of shot gathers. However, because the signals in low NSR parts are much stronger than ESINs, these methods cannot suppress the ESINs in low NSR parts, and they usually damage the signals. In this letter, we propose a deep-learning method to suppress the ESINs in low NSR parts based on a convolutional neural network (CNN). The end-to-end fully convolutional network needs labeled training samples; however, the real data are unlabeled, i.e., the ESINs in low NSR parts are unknown. To obtain the labeled training data, we propose a sample generation method based on real data. The ESINs in high NSR parts extracted by the traditional methods and the signals of the clean shot gathers are added together to synthesize training samples. We then use the synthesized data and its ESINs to train the network. The experiments prove that the proposed method can suppress the ESINs in low NSR parts properly and protect the signals as well.

A framework for attenuation method selection evaluated with ice-penetrating radar data at South Pole Lake

AbstractAll radar power interpretations require a correction for attenuative losses. Moreover, radar attenuation is a proxy for ice-column properties, such as temperature and chemistry. Prior studies use either paired thermodynamic and conductivity models or the radar data themselves to calculate attenuation, but there is no standard method to do so; and, before now, there has been no robust methodological comparison. Here, we develop a framework meant to guide the implementation of empirical attenuation methods based on survey design and regional glaciological conditions. We divide the methods into the three main groups: (1) those that infer attenuation from a single reflector across many traces; (2) those that infer attenuation from multiple reflectors within one trace; and (3) those that infer attenuation by contrasting the measured power from primary and secondary reflections. To assess our framework, we introduce a new ground-based radar survey from South Pole Lake, comparing selected empirical methods to the expected attenuation from a temperature- and chemistry-dependent Arrhenius model. Based on the small surveyed area, lack of a sufficient calibration surface and low reflector relief, the attenuation methods that use multiple reflectors are most suitable at South Pole Lake.

Seismic signal de-noising using time–frequency peak filtering based on empirical wavelet transform

Seismic noise suppression plays an important role in seismic data processing and interpretation. The time–frequency peak filtering (TFPF) is a classical method for seismic noise attenuation defined in the time–frequency domain. Nevertheless, we obtain serious attenuation for the seismic signal amplitude when choosing a wide window of TFPF. It is an unsolved issue for TFPF to select a suitable window width for attenuating seismic noise effectively and preserving valid signal amplitude effectively. To overcome the disadvantage of TFPF, we introduce the empirical wavelet transform (EWT) to improve the filtered results produced by TFPF. We name the proposed seismic de-noising workflow as the TFPF based on EWT (TFPF-EWT). We first introduce EWT to decompose a non-stationary seismic trace into a couple of intrinsic mode functions (IMFs) with different dominant frequencies. Then, we apply TFPF to the chosen IMFs for noise attenuation, which are selected by using a defined reference formula. At last, we add the filtered IMFs and the unprocessed ones to obtain the filtered seismic signal. Synthetic data and 3D field data examples prove the validity and effectiveness of the TFPF-EWT for both attenuating random noise and preserving valid seismic amplitude.

Learning mechanisms in nocebo hyperalgesia: the role of conditioning and extinction processes.

Nocebo hyperalgesia is a clinically relevant phenomenon and may be formed as a result of associative learning, implemented by classical conditioning. This study explored for the first time distinct nocebo conditioning methods and their consequences for nocebo attenuation methods. Healthy participants (N = 140) were recruited and randomized to the following nocebo hyperalgesia induction groups: conditioning with continuous reinforcement (CRF), conditioning with partial reinforcement (PRF), and a sham-conditioning control group. In the attenuation phase, counterconditioning was compared with extinction. During induction, participants experienced increased thermal pain in 100% of nocebo trials in the CRF groups, while in only 70% of nocebo trials in the PRF groups. During evocation, pain stimulation was equivalent across all trials. During attenuation, pain stimulation was decreased on nocebo trials relative to control trials for the counterconditioning groups, while pain remained equivalent across all trials for the extinction groups. Results showed that both PRF and CRF significantly induced nocebo hyperalgesia, but CRF was a more potent nocebo induction method, as compared to PRF. Counterconditioning was more effective than extinction in attenuating nocebo hyperalgesia. Neither CRF nor PRF resulted in resistance to extinction. However, compared with CRF, conditioning with PRF resulted in more resistance to counterconditioning. These findings demonstrate that the more ambiguous learning method of PRF can induce nocebo hyperalgesia and may potentially explain the treatment resistance and chronification seen in clinical practice. Further research is required to establish whether attenuation with counterconditioning is generalizable to clinical settings.