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Rock dynamics as a branch of rock mechanics deal with dynamic behavior of rocks under high loading rates. Considering that many problems in rock engineering including earthquackes, explosions and projectile penetrations deal with high loading rates, rock dynamics has been of high significance to explore. In order to design and stability analysis of many of defense and military structures constructed on and in rocks, designating of dynamic behavior of rocks under different loading rates is essential. However, detailed understanding of rock dynamics has been of high challenge due to the additional ‘4th’ dimension of time. The split Hopkinson pressure bar test (SHPB) is the most applicable and famous technique in determination of dynamic behavior of materials under high loadin rates. In this thechnique, a pressure wave with a high domain is dispatched to the specimen and the reflected and transmitted waves of specimen will be captured by means of strain gauges glued on the bars of Hopkinson apparatus. A dynamic stress-strain curve will be obtained for the specimen applying some known equations upon physical conditions of SHPB test. A great majority of studies have been shown that dynamic strength of rocks increases with an increase in loading rate. Also, it has been shown that inertial and heterogeneity effects are the most impressive factors on dynamic strength increase of rocks under high loading rates. It is of note that Inertial effect boils down to a sudden increase in inner pressure of rock. Although, heterogeneity causes a more proper dynamic stress equilibrium as well as an increase in strain rate of specimen before the failure relative to those of homogenous one. The more the loading rate is, the more the strength of rock increases. In the present study, efforts have been applied to explore the effect of loading rate on dynamic behavior of rocks using split Hopkinson pressure bar as the most known and common apparatus in studying dynamic behavior of materials under high loading rates. The specimens have been cored of the same block of sandstone with a diameter of 21.5 mm and aspect ratio of 2. First of all, some quasi- static tests including uniaxial and Brezilian have been done to obtain uniaxial compressive strength, Young’s modulus, poison’s ratio and tension strength. In the meantime, Ultra-sonic test has been applyied to group the specimens of same p-wave velocity before doing Hopkinson test. The dynamic stress-strain curves for the specimen under different loading rates have been gained after capturing incident, reflected and transmitted waves by the strain gauges. Results show that there is an intense dependence of dynamic strength of sandstone to the loading rate so that with imposing the strain rate of 150 s^(-1) on the specimen, the dynamic strength of sandstone has been increased to 260 MPa from 160 MPa in quasi-static conditions. That’s why DIF, as the ratio of quasi-static strength to the dynamic one, has been obtained 1.6 at the 150 s^(-1) strain rate.

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In this paper, the mechanical behavior of the Graphene Oxide (GO)/ epoxy nanocomposites has been investigated under different strain rates. To reach this goal, GO nano sheets were synthesized through Hummers method (a chemical method) and then GO/epoxy nanocomposite was prepared using the solution-based method. Standard specimens test were made from nanocomposite. In order to study the static and dynamic behavior of material, the static pressure test and the split pressure hopkinson bar test were performed on the specimens, respectively. The results showed that the stiffness and the strength of epoxy increase with adding GO to it. It was found that the behavior of epoxy is dependent on the strain rate so intense that its dynamic strength is more than static one about 50%. Furthermore, the effect of GO in low strain rates is more than high strain rates such that adding 0.3% weight ratio of GO increase the strength of epoxy by nearly 20% and 5% in 0.01 s^(-1) and 1100 s^(-1) of strain rates, respectively. In addition, the comparison of Scanning Electron Microscopy (SEM) images from the fracture surfaces of neat epoxy and its composite showed that the surface toughness of nanocomposite is more than epoxy’s.

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Background: topological data analysis (TDA) in neural network and its advantages over traditional graph theory methods by capturing higher-order relationships and complex structures within the brain examined in this research. TDA provides insights into cognitive processes by analyzing multi-scale interactions among neural activities and is increasingly utilized in both brain science and psychological research.
Methods: The methodology explores neural data from various sources, including multi-electrode arrays (MEAs), to study neural ensemble behaviors and connectivity. Additionally, it critiques existing methods like Granger causality analysis (GCA) for their limitations in interpreting neural data.
Results: According to our findings, the number of spiking activities and active channels rise from the 10th to the 60th day in vitro (DIV). Burst activities peaked between 30 and 50 DIV, while the firing rate in active channels continued to increase until 30 DIV. Furthermore, the average burst length exhibited a consistent rise until 50 DIV. However, the percentage of spikes involved in burst activities displayed a non-monotonic pattern, initially declining until 30 DIV and rising again in subsequent days. The fluctuations in average spike amplitudes can be attributed to factors such as the distance between neurons and electrodes, as well as the ongoing neuronal plasticity and migration.
Conclusion: In summary, TCA provides qualitative insights into network status based on quantitative metrics and established thresholds. While we focused on primary neuronal cells derived from rat cortices, MEA technology is versatile enough to monitor the developmental stages of any neuronal type, including those derived from human sources