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The two-sided bimodality property of Alternate Rician Shadowed (ARS) fading channels makes it a suitable fading model for body-centric wireless communication. The ARS fading model consists of two fluctuating specular components in which only one is active at a time. To provide excellent spectral efficiency with higher quality of service, system transmitter employs an adaptive transmission scheme. This paper derives the exact closed-form expressions of the ARS fading channels capacity. Various adaptive transmission schemes such as channel inversion with a fixed-rate, truncated channel inversion with a fixed-rate, and optimal rate adaptation are considered. A comparison of these schemes is also highlighted. Performance expressions such as binary bit error rate for various coherent and non-coherent modulation schemes and the outage probability are also derived. The derived results are plotted and analyzed for varying fading parameters of the ARS channel. Finally, the results of all performance metrics are verified with Monte-Carlo simulation results. [ABSTRACT FROM AUTHOR]

Resistivity inversion plays a significant role in recent geological exploration, which can obtain formation information through logging data. However, resistivity inversion faces various challenges in practice. Conventional inversion approaches are always time-consuming, nonlinear, non-uniqueness, and ill-posed, which can result in an inaccurate and inefficient description of subsurface structure in terms of resistivity estimation and boundary location. In this paper, a robust inversion approach is proposed to improve the efficiency of resistivity inversion. Specifically, inspired by deep neural networks (DNN) remarkable nonlinear mapping ability, the proposed inversion scheme adopts DNN architecture. Besides, the batch normalization algorithm is utilized to solve the problem of gradient disappearing in the training process, as well as the k-fold cross-validation approach is utilized to suppress overfitting. Several groups of experiments are considered to demonstrate the feasibility and efficiency of the proposed inversion scheme. In addition, the robustness of the DNN-based inversion scheme is validated by adding different levels of noise to the synthetic measurements. Experimental results show that the proposed scheme can achieve faster convergence and higher resolution than the conventional inversion approach in the same scenario. It is very significant for geological exploration in layered formations. [ABSTRACT FROM AUTHOR]

Modified bitumen is a critical material to ensure the durability of asphalt pavements. Traditional polymer-modified bitumen (PMB) has been widely researched and applied in the past two to three decades. Recently, a high-content SBS (Styrene-Butadiene-Styrene) polymer-modified bitumen (HSBSMB) with a higher SBS content of up to 7–9% by weight has started attracting interest from researchers. There are, however, still few specifications or technical guidelines for HSBSMB. To gain a better understanding of HSBSMB, the composition and structure of typical polymer SBS and base bitumen, the micromorphology and micromechanics of HSBSMB, its rheological and aging characteristics, as well as its asphalt mixture and field pavement performance were reviewed comprehensively in this paper. The content covered in this paper is primarily derived from 210 pertinent papers published between 1990 and 2023 in two databases, Web of Science and Google Scholar. It appears from our review that HSBSMB has a stronger internal polymer network than conventional SBSMB and thus exhibits better resistance to rutting, fatigue, and cracking as well as better aging resistance. Furthermore, findings from both laboratory scale and field pavement scale indicate that HSBSMB not only offers higher performance and durability but also leads to reduced pavement structural layer thicknesses in ensuring performance. However, many issues and challenges still remain before HSBSMB will become a viable option for large-scale application in road infrastructure, aspects such as the mechanism of its internal structural changes, the optimization of methods for evaluating its rheological properties, the life cycle assessment of its long-term benefits, as well as the storage stability and workability of HSBSMB. It is hoped that this review will contribute to a better understanding of HSBSMB and promote its application. • The chemical properties of SBS polymer and base bitumen as well as their interactions were comprehensively summarized. • The mechanisms of SBS in bitumen and polymer phase inversion were discussed under different microscopy techniques. • The current standard rheological evaluation methods may need to be improved for high-content SBS polymer-modified bitumen. • High-content SBS polymer-modified bitumen exhibits better resistance to rutting, fatigue, cracking, and aging. [ABSTRACT FROM AUTHOR]

• A neural network-based inversion method that can be used to streamline the acquisition of polymethyl methacrylate (PMMA) material target plate constitutive model parameters for explosive cutting simulations is presented. • The parameters of target plate material constitutive model are derived by parameter inversion and verified by numerical simulation. • The BP neural network-based parameter inversion method not only accurately simulated the jet penetration depth, impact fracture thickness, and spallation thickness of the PMMA target plate, but also effectively characterized the damage features and notch morphology of the damaged areas. • This method ensuring high accuracy while reducing experimental costs and risks compared to traditional methods. In this paper, a neural network-based inversion method that can be used to streamline the acquisition of polymethyl methacrylate (PMMA) material constitutive model parameters for explosive cutting simulations is presented. This approach mitigates the need for multiple tests, a requirement of traditional methods. Initially, three categories of the damage, penetration depth, impact fracture thickness and spallation damage thickness, were distinguished and quantified by cutting the14 mm PMMA target plate with a 2.5 mm wide linear shaped charge, and the adjustment interval for the constitutive model parameters could be determined by combining the explosive cutting experiment data and the empirical parameters of the Johnson Holmquist Ceramics (JH-2) constitutive model. Subsequently, the numerical simulations of the cutting process of the performed target plate tests were carried out using LS-DYNA, and a dataset of target plate damage incorporating the three types of damage data was amassed. Ultimately, a neural network model correlating the parameters of the PMMA target plate constitutive model with the damage data was developed and trained using the plate damage dataset, and several supplementary experiments as well as finite element numerical simulations involving a 4.2 mm wide linear shaped charge cutting a 19 mm PMMA target plate were conducted. The numerical results displayed minimal variance from the experimental results in terms of fracture characteristics and damage data, suggesting that the inverted JH-2 constitutive model parameters can be effectively applied to PMMA target plate explosive cutting simulations. The parameter inversion method allows for the acquisition of more accurate material constitutive model parameters with fewer experiments and will be beneficial for further theoretical studies and practical applications of target plates in the future. [ABSTRACT FROM AUTHOR]