Repetition Interval Research Articles

LSTM을 사용한 펄스 레이다 신호 속성 분류

In this study, the feature attributes from a received pulse radar signal are defined and certain methods are proposed to classify the attributes using machine learning. The classifier is composed of a long short-term memory (LSTM) network and a fully-connected neural network. As inputs to the LSTM network, pulse repetition interval and radio frequency are used among the pulse description words. The outputs of the classifier can be organized into three types of attributes, i.e., the change pattern of the pulse repetition interval and radio frequency, the number of steps in a period, and the number of pulses in a step. Two classifier structures, single-input and multiple-input, are proposed according to the number of input types. The number of classes varies depending on the classifier structure and the multiple-input classifier classifies 22,410 radar signal attribute sets. The missing pulses, the introduction of any non-desired pulses, and an error in measuring the pulse features are considered as the non-ideal characteristics of the pulse train. The simulation results show that the proposed method shows a high classification accuracy despite the large number of classification options.

Online adaptive dwell scheduling based on dynamic template for PAR

An adaptive dwell scheduling algorithm for phased array radar (PAR) is proposed in this paper. The concept of online dynamic template is introduced, based on which a general pulse interleaving technique for PAR is put forward. The pulse interleaving condition of the novel pulse interleaving is more intuitive and general. The traditional adaptive dwell scheduling algorithm combined with the general novel pulse interleaving technique results in the online adaptive dwell scheduling based on dynamic template for PAR is given. The proposed algorithm is suitable for radar tasks with multiple pulse repetition intervals (PRIs), which can be utilized in the actual radar system. For the purpose of further improving the scheduling efficiency, an efficient version is proposed. Simulation results demonstrate the effectiveness of the proposed algorithm and the efficient one. The proposed efficient algorithm can improve the time utilization ratio (TUR) by 9%, the hit value ratio (HVR) by 3.5%, and reduce the task drop ratio (TDR) by 6% in comparison with existing dwell scheduling algorithms considering pulse interleaving in PAR and the proposed efficient one.

One-bit splitting deceptive jamming against SAR

One-bit quantization is a promising technique due to its performance retention and complexity reduction in a deceptive jammer against synthetic aperture radar (SAR). In this paper, the 1-bit quantization technology is utilized to agilely generate split false targets in the SAR imagery once the radar signal is intercepted, which reduces the complexity of the jammer significantly with guaranteed focusing quality. A single-frequency threshold is used to decompose harmonics incurred by the 1-bit quantization, and its parameters are adjusted through different pulse repetition intervals to provide steerable modulations. In this way, the SAR signal is split into coupled false scatterers during the 1-bit interception. By further deploying amplitude, time-delay, and Doppler frequency modulations on the 1-bit intercepted signal, the split false targets are created. The proposed approach is compared with different deceptive jamming methods to show its validity in effectiveness and cost, and numerical experiments are also presented for verification.

UAV swarm based radar signal sorting via multi-source data fusion: A deep transfer learning framework

Traditional clustering algorithms can be applied for the pre-sorting step of radar signal sorting. It can effectively dilute the pulse stream and prevent the dense pulse stream from interfering pulse repetition interval (PRI) extraction. However, the pre-sorting deviation will cause interference and missing pulses during the main sorting process. To solve this problem, we deploy the unmanned aerial vehicle (UAV) swarm to monitor reconnaissance areas and put forward a novel deep transfer learning based signal sorting method. The UAV swarm can collect the pulses from different time and spatial domains, and interference and missing pulses in main sorting processing can be relieved dramatically. In our model, we pre-train our model with the data collected from multiple source areas, which corresponds to different areas detected by different parts of UAV swarms. Then we fine-tune our model with the data of the target area. The experimental results prove that the signal sorting accuracy of methods based on deep transfer learning, i.e., YOLO-MobileNet, F-RCNN and cascade RCNN, are higher than that of the baseline methods. In addition, the signal sorting accuracy of traditional methods based on deep learning can be greatly improved with the help of transfer learning.

Ultrasonication promotes extraction of antioxidant peptides from oxhide gelatin by modifying collagen molecule structure

This study primarily explored the internal mechanism underlying the ultrasonication-induced release of antioxidant peptides. An oxhide gelatin solution was treated ultrasonically (power = 200, 300, and 400 W), followed by enzymatic hydrolysis and structural and morphological analysis. The results showed that ultrasonication increased not only the degree of hydrolysis (DH) and protein recovery rate of the oxhide gelatin but also the ABTS radical scavenging, DPPH radical scavenging, ferrous chelating, and ferric reducing activities of its hydrolysate. The oxhide gelatin hydrolysate treated with 300-W ultrasonication had the maximum antioxidant activities. Ultrasonication inhibited hydrogen bond formation, reduced the crosslinking between collagen molecules, transformed part of the folded structure into a helical structure, and lowered the thermal stability of collagen molecules. The micromorphological analysis revealed that ultrasonication caused the gelatin surface to become loose and develop cracks, and as the power of the ultrasonication increased, the repetition interval distance (dÅ) also increased. Moreover, ultrasonication improved the solubilization, surface hydrophobicity, and interface characteristics and increased the content of basic and aromatic amino acids in the hydrolysate. In conclusion, ultrasonication modifies the protein structure, which increases the enzyme’s accessibility to the peptide bonds and further enhances antioxidant peptide release. These findings provide new insights into the application of ultrasonication in the release of antioxidant peptides.

Combining active and passive acoustic methods to image hydraulic fracture growth in laboratory experiments

We combine active and passive acoustic measurements to improve the spatio-temporal imaging of hydraulic fracture growth performed under true triaxial confinement in the laboratory. 64 active piezo-electric transducers (54 P waves, 10 S waves) work in source (32) - receivers (32) mode to perform an acoustic survey at repetitive intervals (every 10 seconds) during a hydraulic fracture growth experiment. The analysis of the evolution of the active acoustic monitoring changes allow to image the evolution of the fracture front (via an inversion of the active acoustic waves diffracted by the fracture front). An additional 16 piezoelectric transducers are pre-amplified and work in passive mode continuously recording at 10MHz. We present a nearly-automatic passive signal processing, acoustic emission detection, and location algorithm. This allows to record, detect and to locate acoustic emissions associated with fracture initiation and growth in between the active acoustic measurement sequences. Using a hydraulic fracturing test performed in gabbro, we discuss how active and passive acoustic monitoring complements one another and bring different type of information on hydraulic fracture growth.

Automatic recognition of pulse repetition interval modulation using temporal convolutional network

Pulse Repetition Interval (PRI) modulation recognition is a key issue in radar identification process in modern electronic intelligent (ELINT) and electronic support measure (ESM) systems. In this study, a novel approach based on the intrinsic property of the temporal convolutional network (TCN) is presented for PRI modulation type recognition. Since a causal TCN is used for this purpose, the method is suitable for online ESM and ELINT analysis. The simulation results show that the method accurately classifies seven types of PRI modulation including simple, dwell and switch, stagger, jitter, agile, sliding and periodic modulations in realistic scenarios. In order to investigate the performance of the method when the problem of missing or spurious pulses occurs, the impacts of these problems are examined, separately and together, on the recognition process. It is shown that the method works effectively even with a relatively high percentage of missing and/or spurious pulses (up to 30%). The method also works effectively in the presence of unintentional jitter and large outliers, which can be due to radar antenna scan. The experimental results on real data confirm that the proposed method performs accurately and effectively in real world scenarios.

Measurement of flow velocity vectors in carotid artery using plane wave imaging with repeated transmit sequence.

Doppler-based methods are widely used for blood flow imaging in clinical settings. However, they inherently estimate the velocity component only in the axial direction. Therefore, various studies of angle-independent methods have been conducted. The multi-angle Doppler method is one such angle-independent method, in which the velocity vector is estimated using axial velocities obtained from multiple directions by steering an ultrasonic beam. Recently, plane wave imaging, which realizes a very high frame rate of several thousand frames per second, was applied to the multi-angle Doppler method. However, the maximum detectable velocity, i.e., the aliasing limit, was reduced depending on the number of steering angles. In the present study, the feasibility of a specific transmit sequence, namely, the repeated transmit sequence, was examined using the plane-wave multi-angle Doppler method. In the repeated transmit sequence, plane waves were emitted to the same direction twice, after which the steering angle was changed. By repeating the same procedure, a pair of beamformed radio-frequency (RF) signals could be obtained under each beam steering angle. By applying the autocorrelation method to each pair of RF signals, the time interval between the RF signals could be kept as the pulse repetition interval (PRI). The feasibility of such a transmit sequence was examined by numerical simulation and in vivo measurement of a human carotid artery. The simulation results showed that the maximum steering angles of over 10 degrees were not feasible with the linear array used in the present study. The feasible maximum steering angle would depend on the element pitch of the probe relative to the ultrasonic wavelength. By limiting the maximum steering angles to 5 and 10 degrees, bias errors were 9.2% and 11.3%, respectively, and root mean squared errors were 21.5% and 16.9%, respectively. Also, flow velocity vectors in a human carotid artery could be visualized with the proposed method. The multi-angle Doppler method was implemented in plane wave imaging with the repeated transmit sequence, and the proposed method was shown to be feasible through numerical simulation and in vivo measurement of a carotid artery.

Recognizing and Counting Freehand Exercises Using Ubiquitous Cellular Signals.

Freehand exercises help improve physical fitness without any requirements for devices or places. Existing fitness assistant systems are typically restricted to wearable devices or exercising at specific positions, compromising the ubiquitous availability of freehand exercises. In this paper, we develop MobiFit, a contactless freehand exercise assistant using just one cellular signal receiver placed on the ground. MobiFit passively monitors the ubiquitous cellular signals sent by the base station, which frees users from the space constraints and deployment overheads and provides accurate repetition counting, exercise type recognition and workout quality assessment without any attachments to the human body. The design of MobiFit faces new challenges of the uncertainties not only on cellular signal payloads but also on signal propagations because the sender (base station) is beyond the control of MobiFit and located far away. To tackle these challenges, we conducted experimental studies to observe the received cellular signal sequence during freehand exercises. Based on the observations, we constructed the analytic model of the received signals. Guided by the insights derived from the analytic model, MobiFit segments out every repetition and rest interval from one exercise session through spectrogram analysis and extracts low-frequency features from each repetition for type recognition. Extensive experiments were conducted in both indoor and outdoor environments, which collected 22,960 exercise repetitions performed by ten volunteers over six months. The results confirm that MobiFit achieves high counting accuracy of 98.6%, high recognition accuracy of 94.1% and low repetition duration estimation error within 0.3 s. Besides, the experiments show that MobiFit works both indoors and outdoors and supports multiple users exercising together.

Continuous PRI Variation and Phase Center Adjustment for Azimuth Uniform Sampling in Staggered SAR

Staggered synthetic aperture radar (SAR) can effectively stagger range blind areas by periodically changing the pulse repetition interval (PRI), to achieve continuous imaging with an ultrawide swath. In conventional staggered SAR, azimuth samples are nonuniformly distributed due to the variable PRI, and complex resampling processing, such as best linear unbiased (BLU) interpolation and multichannel reconstruction processing, is required. In this article, a strict rule of PRI variation and phase center adjustment (PCA) is proposed for staggered SAR, to solve the problem of nonuniform azimuth sampling. In the proposed joint strategy of PRI variation and PCA, the relevant parameters for PCA are first determined. Then, the PRI sequence is designed according to PCA parameters to stagger blind ranges. Finally, the PCA rule is designed according to the designed PRI sequence and PCA parameters. During the data acquisition interval, the effective phase center is periodically adjusted pulse by pulse according to this rule, making the azimuth samples totally uniformly distributed. In addition, the discontinuously distributed missing samples can be estimated by signal estimation approaches. With the proposed joint rule of PRI variation and PCA, the emergence of false targets in imaging results can be avoided, and the complex resampling processing can be relieved to reduce the computational complexity. Simulation experiments on imaging results verify the advantages of this strategy.

Reconstruction algorithm for staggered synthetic aperture radar with modified second-order keystone transform

Staggered synthetic aperture radar (SAR), which operates with pulse repetition interval (PRI) variation, deals with the blind range problem caused by constant PRI in conventional high-resolution wide-swath SAR imaging. Due to the variation of PRI, there appear periodic loss of pulses and nonuniform sampling in azimuth. However, the exiting reconstruction methods mostly correct range curvature after resampling the nonuniform samplings into a uniform grid. It inevitably introduces the errors and thus affects the effectiveness of the correction. To solve the nonuniform sampling problem and eliminate the errors, our study proposes a reconstruction algorithm [reconstruction algorithm with modified second-order keystone transform (RMSKT)] with modified second-order keystone transform in staggered SAR mode. Moreover, to provide a priori knowledge required by the reconstruction, i.e., the nonuniform sampling distribution, which depends on PRI variation, our study first designs an optimal PRI variation scheme and optimizes the sequence parameters. With the designed PRIs sequence, the proposed RMSKT algorithm can achieve nonuniform range curvature correction and data reconstruction jointly. The proposed RMSKT algorithm shows significant improvements over the traditional reconstruction methods in terms of the peak-sidelobe ratio, the integral sidelobe ratio, and the azimuth ambiguity-to-signal ratio. Simulations and experiments on raw data generated in staggered mode are performed to verify the effectiveness of the proposed method.

Doppler disambiguation in MIMO FMCW radars with binary phase modulation

Multiple-input multiple-output arrays in frequency modulated continuous wave (FMCW) radars provide the angular resolution required to isolate objects in complex automotive scenes. However, the demodulation of individual antenna contributions increases the chirp repetition interval, which reduces the maximum unambiguously measurable velocity. Objects moving faster than this velocity are then incorrectly folded in the range-Doppler maps, leading to critical inaccuracies in the advanced driver assistance systems. Here, this problem is addressed from the binary phase modulation (BPM) perspective, which is a scheme particularly attractive due to its high signal-to-noise ratio, and whose intrinsic phase alterations prevent traditional disambiguation techniques from being reliable. The authors present a detailed analysis on the design, implementation, and validation of Doppler disambiguation techniques for BPM systems. The presented benchmark includes a variety of algorithms involving the Chinese remainder theorem, density-based spatial clustering of applications with noise (DBSCAN), hypothetical phase compensation, and an intuitive range-based approach. The techniques are extensively validated using synthetic data generated with MATLAB, and real data collected with a 77-GHz FMCW radar. The results show the best set of trade-offs for the enhanced DBSCAN (EDBSCAN) method in terms of robustness, computational overhead, velocity span, and disambiguation rate.

Theoretical Minimum Detection Range for a Rapidly Moving Target and an Experimental Evaluation

There have been considerable challenges with radar systems for detecting high-speed projectiles at a short range. This necessitates the presentation of a guideline for the minimum detection range that will guarantee detection of a target. In this letter, the detection range for a rapidly flying target is studied based on the characteristics of the target, such as speed and launch angle, and radar parameters such as pulse repetition interval, dwell time, beamwidth, and so on. The derived equation was applied to parametric studies for different characteristics of targets in order to investigate the influential parameters that affect the minimum detection range. A field test using the radar system’s prototype was performed to evaluate the validity of the proposed equation.

Are mode-specific differences in performance fatigability attributable to muscle oxygenation?

The purpose of this study was to examine the composite, intra-individual, and inter-individual patterns of responses for deoxygenated hemoglobin and myoglobin (deoxy[heme]), oxygenated hemoglobin and myoglobin (oxy[heme]), total hemoglobin and myoglobin (total[heme]), and tissue saturation index (StO2%) during fatiguing, maximal, isokinetic, unilateral, and bilateral leg extensions. Nine men (Mean ± SD; age = 21.9 ± 2.4 years; height = 181.8 ± 11.9cm; body mass = 85.8 ± 6.2kg) performed 50 unilateral and bilateral maximal, concentric, isokinetic leg extensions at 180°s-1 on two separate visits. The muscle oxygenation parameters assessed with near-infrared spectroscopy from the dominant leg and isokinetic torque were averaged for 2 consecutive repetitions at 5 repetition intervals. Separate 2 (Condition [Unilateral and Bilateral]) × 10 (Repetition [5-50]) repeated measures ANOVAs were performed to examine mean differences for normalized isokinetic torque and each muscle oxygenation parameter. Intra- and inter-individual differences were examined with polynomial regression analyses. For normalized isokinetic torque, the unilateral condition (56.3 ± 10.5%) exhibited greater performance fatigability than the bilateral condition (45.0 ± 18.7%). Collapsed across Condition, deoxy[heme] exhibited an increase (p < 0.001), while StO2% exhibited a decrease (p < 0.001). The bilateral condition exhibited a more sustained decline in oxy[heme] than the unilateral condition (p = 0.005). Deoxy[heme], oxy[heme], and total[heme] exhibited substantial intra- and inter-individual differences for the fatigue-induced patterns of response. The present findings indicated that the greater performance fatigability for unilateral versus bilateral fatiguing, maximal, isokinetic leg extensions was not attributable to differences in muscle oxygenation. Future studies of muscle oxygenation should report individual and composite fatigue-induced patterns of responses due to the substantial intra- and inter-individual variabilities.

Pulse deinterleaving based on fusing PDWs and PRI extraction process for radar-assisted edge devices considering computational costs

Deinterleaving or radar pulse separation is a very important goal in terms of radar sources for identifying and implementing electronic warfare systems. In order to separate radar pulses, parameters measured by electronic warfare receivers such as electronic warfare support measures (ESM) and electronic signals intelligence (ELINT) are used in pulse separation. This paper presents a multi-parameter improved method for separating the pulse sequence of radar signals based on time of arrival (TOA) processing with sorting the other pulse descriptor words (PDW) parameters. In the proposed method, after extracting all the pulse repetition intervals (PRIs) based on TOA, the parameters of the angle of arrival, pulse width and carrier frequency (RF) are being used in pulse sorting to separate the received interleaved pulse sequences. The sequential difference histogram (SDIF) algorithm or cumulative difference histogram (CDIF) algorithm is used to extract all pulse repetition intervals. Also, in order to separate the sequence of the received pulses from all surroundings emitters, in addition to matching the potential PRI among the TOAs of the pulses and the similarity measurement in the other parameters of the pulse sequence (pulse sorting) have been used. This proposed algorithm is implemented in the integrated and complete design for deinterleaving of the radar pulses. The proposed method by considering low-cost computing sources considers a fast and low-complexity solution that can be used for edge-enabled distributed processors in aerial radar platforms as edge devices for military/combat unmanned aerial vehicles or networked missiles. The simulation results show that our method is completely effective.

Workout Pacing Predictors of Crossfit® Open Performance: A Pilot Study.

To observe workout repetition and rest interval pacing strategies and determine which best predicted performance during the 2016 CrossFit® Open, five male (34.4 ± 3.8 years, 176 ± 5 cm, 80.3 ± 9.7 kg) and six female (35.2 ± 6.3 years, 158 ± 7 cm, 75.9 ± 19.3 kg) recreational competitors were recruited for this observational, pilot study. Exercise, round, and rest time were quantified via a stopwatch for all competitors on their first attempt of each of the five workouts. Subsequently, pacing was calculated as a repetition rate (repetitions·s-1) to determine the fastest, slowest, and average rate for each exercise, round, and rest interval, as well as how these changed (i.e., slope, Δ rate / round) across each workout. Spearman’s rank correlation coefficients indicated that several pacing variables were significantly (p < 0.05) related to performance on each workout. However, stepwise regression analysis indicated that the average round rate best predicted (p < 0.001) performance on the first (R2 = 0.89), second (R2 = 0.99), and fifth (R2 = 0.94) workouts, while the competitors’ rate on their slowest round best predicted workout three performance (R2 = 0.94, p < 0.001). The wall ball completion rate (R2 = 0.89, p = 0.002) was the best predictor of workout four performance, which was improved by 9.8% with the inclusion of the deadlift completion rate. These data suggest that when CrossFit® Open workouts consist of multiple rounds, competitors should employ a fast and sustainable pace to improve performance. Otherwise, focusing on one or two key exercises may be the best approach.

Automatic pulse repetition pattern reconstruction of conventional radars

Signals of radars with fixed, stagger and other conventional pulse repetition intervals (PRI) occupy a large proportion in most radar reconnaissance datasets. Automatic and accurate reconstruction of the PRI patterns of these radars is an important task in realizing intelligent processing of radar reconnaissance data. In order to address this problem, this article proposes an automatic method based on the extraction and extension of frequent differential time-of-arrival (DTOA) items, which can be combined with other pulse parameters such as pulse width. The values and ordering of the frequent items are determined to reconstruct a complete PRI cycle, and the radar pulses are deinterleaved at the same time as a by-product. Compared with the commonly used one-dimensional radar reconnaissance parameters such as framework PRI or typical PRI set, the reconstructed PRI pattern contains more information about radar operational modes and can be applied to realize online and parallel pulse deinterleaving and more accurate radar type classification.

A Signal Processing Algorithm of Two-Phase Staggered PRI and Slow Time Signal Integration for MTI Triangular FMCW Multi-Target Tracking Radars.

In this paper, a novel signal processing algorithm for mitigating the radar blind speed problem of moving target indication (MTI) for frequency modulated continuous wave (FMCW) multi-target tracking radars is proposed. A two-phase staggered pulse repetition interval (PRI) solution is introduced to the FMCW radar system. It is implemented as a time-varying MTI filter using twice the hardware resources as compared to a uniform PRI MTI filter. The two-phase staggered PRI FMCW waveform is still periodic with a little more than twice the period of the uniform PRI radar. We also propose a slow time signal integration scheme for the radar detector using the post-fast Fourier transformation Doppler tracking loop. This scheme introduces dB of extra signal processing gain to the signal before the radar detector compared with the original uniform PRI FMCW radar. The validation of the algorithm is done on the field programmable logic array in the loop test bed, which accurately models and emulates the target movement, line of sight propagation and radar signal processing. A simulation run of tracking s of the target movement near or at the radar blind speed shows that the total degradation from the raw post-fast Fourier transformation received signal to noise ratio is about dB. With a dB post-processing signal to noise ratio of the proposed algorithm for the moving target at around a km range and with about a dB m2 radar cross section at a GHz carrier frequency, the tracking errors of the two-dimensional angles with a digital phased array are less than degree. The range tracking error is about m.

Fast Generation of Deceptive Jamming Signal Against Spaceborne SAR Based on Spatial Frequency Domain Interpolation

This article proposes a novel method for the generation of the deceptive jamming signal against spaceborne SAR, which can calculate the jammer’s frequency response (JFR) efficiently. The first advantage of this algorithm is that the real-time computational complexity is independent of the number of fake scattering units, so it is particularly suitable for generating scenes containing a large number of scatterers. Besides, the imaging quality of fake targets is also improved significantly, especially in the case of squint geometries. First, using the Taylor series expansion and approximations, we derive the recurrence relationship of the slant range between the adjacent pulse repetition intervals. Based on this relationship, the JFR at each azimuth time is mapped to a special spatial spectrum, which is the 2-D Fourier transform along the range and azimuth dimensions of the JFR matrix at the time of the first pulse arrival. Therefore, after the initial JFR is calculated, the subsequent JFRs can be quickly obtained by sinc function interpolation. Then, the validity and effective region of this algorithm are estimated by the theoretical analysis of the slant range error. The simulation results and a computational complexity analysis verify that the algorithm demonstrates superior performance in terms of imaging quality and efficiency.

The Effect of Reperfusion on Cerebral Activity in Donors after Circulatory Death Following Normothermic Regional Perfusion

Purpose To investigate brain activity and intracerebral physiological parameters following no-touch and normothermic regional perfusion (NRP) in donors after circulatory death. Methods The study comprised 16 female pigs of 85 kg. Following anesthesia, five burr holes were placed in the skull targeting the parasagittal cortex bilaterally. To assess cortical brain activity two needles were used to record electroencephalography (EEG) and somatosensory evoked potentials (SSEP). Two probes measuring intracranial pressure and cerebral blood perfusion (CBF), temperature, and oxygen were inserted. Additionally, a microdialysis catheter for metabolic monitoring of lactate, pyruvate, glycerol, and glucose was inserted. The animals were cannulated for the heart-lung machine and baseline measurements were performed before withdrawal from life support. Before NRP, the animals were randomized into two groups: Clamp or non-clamp of the aortic arch vessels. After mechanical asystole, a no-touch period of 8 minutes was observed before the institution of NRP. The animals were weaned from NRP after 30 minutes and subsequently monitored for 3 hours after weaning. Results In the clamp group, flatline EEG and no-SSEPs were recorded after weaning in all pigs. In the non-clamp group, SSEPs were observed after weaning in 6/8 pigs. In all pigs, a peculiar EEG activity of periodic 4-5 Hz complexes, amplitude up to 300 μV, with a repetition interval of one in every 8-60 seconds was recorded. In two pigs, continuous EEG activity was observed alongside the periodic complexes. Additionally, spontaneous respiratory movements were observed in 6/8 pigs in the non-clamp group during a brief pause of ventilation. Preliminary analysis of intracranial measurements of CBF, oxygen, and temperature indicates successful occlusion of the arch vessels in the clamp group and as such cessation of cerebral perfusion. All results await final statistical analysis. Conclusion Some degree of cerebral function returns following circulatory death and resuscitation with NRP and cerebral reperfusion. We observed continuous EEG activity alongside periodic complexes resembling the so-called Nu-complexes thought to originate in the hippocampus. In addition, SSEP response and negative apnea tests suggest that brain stem function returns following NRP with preserved cerebral perfusion.