A complete framework of predicting the attributes of sea clutter under different operational conditions, specified by wind speed, wind direction, grazing angle, and polarization, is proposed for the first time. This framework is composed of empirical spectra to characterize sea-surface profiles under different wind speeds, the Monte Carlo method to generate realizations of sea-surface profiles, the physical-optics method to compute the normalized radar cross-sections (NRCSs) from individual sea-surface realizations, and regression of NRCS data (sea clutter) with an empirical probability density function (PDF) characterized by a few statistical parameters. JONSWAP and Hwang ocean-wave spectra are adopted to generate realizations of sea-surface profiles at low and high wind speeds, respectively. The probability density functions of NRCSs are regressed with K and Weibull distributions, each characterized by two parameters. The probability density functions in the outlier regions of weak and strong signals are regressed with a power-law distribution, each characterized by an index. The statistical parameters and power-law indices of the K and Weibull distributions are derived for the first time under different operational conditions. The study reveals succinct information of sea clutter that can be used to improve the radar performance in a wide variety of complicated ocean environments. The proposed framework can be used as a reference or guidelines for designing future measurement tasks to enhance the existing empirical models on ocean-wave spectra, normalized radar cross-sections, and so on.

OBJECTIVE: In recent years, advances in ultrasonographic techniques have allowed the detection of even small hepatocellular carcinomas. However, many cases do not show distinctive ultrasonographic features. A quantitative ultrasonographic procedure for making the diagnosis would therefore be desirable. It is recognized that radio-frequency (RF) signals from hepatic tumors conform to the K distribution. The K distribution is used for the characterization of the statistical properties of backscattering signals from heterogeneous regions. In this study, RF signals were acquired from hemangioma of the liver (hemangioma) and hepatocellular carcinoma (HCC), and parameters of the K distribution, i.e., φ (the mean square of the amplitude of RF signals) and α (the number of effective scatterers), were calculated for the quantitative ultrasonographic evaluation of hepatic tumors.
METHODS: This study included 10 nodules of 10 patients with hemangioma and 27 nodules of 24 patients with HCC. The A-mode RF signals passing through the hepatic tumors were acquired with an Aloka SSD-1000 ultrasound system, and measurement units comprising 279 points were set on the RF signals corresponding to the tumor lesion. The parameters of the K distribution that were most consistent with the histogram were calculated and assessed.
RESULTS: With regard to φ, the values were high in hemangioma, and there was a significant (P < 0.05) difference in the φ value between hemangioma and HCC. On the other hand, there was no significant difference in the α value between hemangioma and HCC.
CONCLUSIONS: The α values of hemangioma were equivalent to those of HCC, while the φ values for hemangioma were higher than those for HCC. It was deduced from these observations that a situation in which an electron beam is likely to scatter exists in the tumor. This is also consistent with the pathological findings reported from previous studies. The use of these parameters is expected to allow quantitative ultrasonographic evaluation of hepatic tumors.

Accurate differentiation of the proportion of bioconcentrated metals (i.e. incorporated into cells) and the proportion that is not bioconcentrated (i.e. adsorbed at the surface) would lead to a better understanding of the uptake processes and would represent an advance in the use of mosses as biomonitors. Traditionally the methods used to remove contaminants that are not bioconcentrated were to wash the plant material with water or to apply the sequential elution technique, but nowadays both options are considered inaccurate for these purposes. The remaining possibilities are to clean the moss samples with a nitrogen jet or by power ultrasound. Samples of terrestrial moss Pseudoscleropodium purum (Hewd.) Fleisch. were collected from five sampling stations. Different nitrogen jet cleaning procedures and ultrasound cleaning procedures were applied to the mosses. To determine whether any of the treatments altered the membrane integrity of the moss samples, the concentrations of K were determined. The shoots were observed under a scanning electron microscope, and the size and number of particles were determined. Nitrogen jet cleaning was determined to be unacceptable because it damaged the phyllids and/or altered the membrane permeability and did not eliminate the particles from the moss surface. Moreover, ultrasound cleaning treatment should also discarded because of the loss of extracellular metals that are transferred to the water in which the moss is cleaned.