Reliable assessment of the fatigue resistance of asphalt pavement with a long-term service is critically crucial for the rational formulation of original pavement utilization strategies in reconstruction and expansion projects. Currently, the pavement performance evaluation indicators are mainly used to guide pavement preventive maintenance, and its applicability in reconstruction and expansion projects of the freeway is limited. This paper aims to propose an evaluation method of fatigue resistance of asphalt concrete utilizing semi-circular bending (SCB) tests and stereo digital image correlation (stereo-DIC) techniques. A total of 27 asphalt concrete cores were drilled from the three freeways (K84, K124, and K165) with a service life of more than 20 years, and the SCB specimens were produced to conduct the SCB fracture and fatigue tests. During the SCB test, the stereo-DIC technique was employed to monitor the evolution process of the strain distribution and crack length for the specimens. K-dimension tree neighbor-searching algorithm (K-d tree algorithm) was used to effectively measure the change of crack length corresponding to each fatigue load cycle. Meanwhile, the strain threshold of asphalt concrete crack initiation was determined by the bilinear softening cohesive zone model (CZM) to ensure the accuracy of the crack length calculated by the K-d tree algorithm. Furthermore, the relationship between crack growth rate and stress intensity, which was used to fit the Paris law parameters, was determined. The CZM and DIC results indicated that the strain threshold of asphalt concrete crack should be set as 2000 με when using the K-d tree algorithm to determine the crack length. With the stress ratio increase, the Paris law parameter A increased wavily, and the parameter n decreased steadily, while the threshold of the stress intensity factor increased steadily. The Paris law master curves could characterize the fatigue performance of various road sections at a wide load range. The residual fatigue life of K84, K124, K165 the road sections were 2.13E + 08, 3.57E + 08, and 1.02E + 07, respectively.

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Romano et al. show that cerebellar Purkinje cell activity follows the respiratory rhythm during rest. Triggered by sensory input, Purkinje cells can alter their activity and thereby accelerate the timing of the next inspiration. Concomitantly, they also augment whisker movements, highlighting a coordinating role in aligning autonomic and sensorimotor behaviors.

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The rodent whisker system is a prominent experimental subject for the study of sensorimotor integration and active sensing. As a result of improved video-recording technology and progressively better neurophysiological methods, there is now the prospect of precisely analyzing the intact vibrissal sensorimotor
system. The vibrissae and snout analyzer (ViSA), a widely used algorithm based on computer vision and image processing, has been proven successful for tracking and quantifying rodent sensorimotor behavior, but at a great cost in processing time. In order to accelerate this offline algorithm and eventually
employ it for online whisker tracking (less than 1 ms/frame latency), we have explored various optimizations and acceleration platforms, including OpenMP multithreading, NVidia GPUs and Maxeler Dataflow Engines. Our experimental results indicate that the optimal solution for an offline implementation of ViSA is
currently the OpenMP-based CPU execution. By using 16 CPU threads, we achieve more than 4,500x speedup compared to the original Matlab serial version, resulting in an average processing latency of 1.2 ms/frame, which is a solid step towards real-time (and online) tracking. Analysis shows that running the algorithm on a 32-thread-enabled machine can reduce this number to
0.72 ms/frame, thereby enabling real-time performance. This will allow direct interaction with the whisker system during behavioral experiments. In conclusion, our approach shows that a combination of software optimizations and the careful selection of hardware platform yields the best performance increase.@en