We describe an algorithm to estimate the instantaneous power spectral density (PSD) of nonstationary signals. The algorithm is based on a dual Kalman filter that adaptively generates an estimate of the autoregressive model parameters at each time instant. The algorithm exhibits superior PSD tracking performance in nonstationary signals than classical nonparametric methodologies, and does not assume local stationarity of the data. Furthermore, it provides better time-frequency resolution, and is robust to model mismatches. We demonstrate its usefulness by a sample application involving PSD estimation of intracranial pressure signals (ICP) from patients with traumatic brain injury (TBI).
Selenium nanoparticles (SeNPs) with diameters from 64.8 to 110.1 nm were successfully synthesized by γ-irradiation of solutions containing Se4+ and water-soluble yeast β-glucan. The size and size distribution of SeNPs were analyzed by dynamic light scattering (DLS). Analytical X-ray diffraction (XRD) pattern results confirmed the crystal structure of the Se nanoparticles and Fourier transform infrared (FTIR) spectroscopy revealed that β-glucan could interact with SeNPs through steric (Se…O) linkages leading to a homogeneous and translucent solution state for 60 days without any precipitates. In vivo tests in cytoxan-induced immunosuppressed mice revealed that the daily supplementation of SeNPs/β-glucan at concentrations of 6 mg per kg body weight of tested mice significantly stimulated the generation of cellular immune factors (white blood cells, neutrophil, lymphocyte, B cells, CD4+ cells, CD34+ cells and natural killer cells) and humoral immune indexes (IgM, IgG, TNF-α, IFN-γ and IL-2) in peripheral blood, bone marrow and spleen of the immunosuppressed mice. The obtained results indicated that radiation-synthesized SeNPs/β-glucan may be a candidate for further evaluation as an agent for the prevention of immunosuppression in chemotherapy.
In this paper, we present a control method for a quadruped walking robot inspired from the locomotion of quadrupeds. A simple and useful framework for controlling a quadruped walking robot is presented, which is obtained by observing the stimulus-reaction mechanism, the gravity load receptor and the manner of generating repetitive motions from quadrupeds. In addition, we propose a new rhythmic pattern generator that can relieve the large computational burden on solving the kinematics. The proposed method is tested via a dynamic simulation and validated by implementation in a quadruped walking robot, called AiDIN-I (Artificial Digitigrade for Natural Environment I).
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