Discrimination of land cover from a multiparameter SAR data set

The identification of the most valuable radar observation parameters (e.g., frequency, polarisation, incidence angle) is important both for designing nonredundant high-performance sensors (i.e. selection of frequency bands and polarisations) and for specifying mission operation requirements (i.e. temporal sampling, incidence angle). Moreover, the task of classifying multiparameter SAR images may require to adopt a strategy that implies the selection of a number of features among those available fromthis kind of sensors. In this paper we have performed this kind of analysis in a specific area of interest to account for the particular conditions in which remotely sensed data are going to be used. The paper summarises the results of the analysis of the radar data acquired during the MAC Europe ’91 and X-SAR/SIR-C campaigns over the Montespertoli test site in Italy. The analysis is based mainly on a statistical approach aiming at demonstrating what is the contribution of different measurements performed by the polarimetric SAR for discriminating the surface coverage. The work is intended to furnish a guideline to develop an optimal strategy for acquiring and processing polarimetric data to be used for land classification

Discrimination of land cover from a multiparameter SAR data set

The identification of the most valuable radar observation parameters (e.g., frequency, polarisation, incidence angle) is important both for designing nonredundant high-performance sensors (i.e. selection of frequency bands and polarisations) and for specifying mission operation requirements (i.e. temporal sampling, incidence angle). Moreover, the task of classifying multiparameter SAR images may require to adopt a strategy that implies the selection of a number of features among those available fromthis kind of sensors. In this paper we have performed this kind of analysis in a specific area of interest to account for the particular conditions in which remotely sensed data are going to be used. The paper summarises the results of the analysis of the radar data acquired during the MAC Europe ’91 and X-SAR/SIR-C campaigns over the Montespertoli test site in Italy. The analysis is based mainly on a statistical approach aiming at demonstrating what is the contribution of different measurements performed by the polarimetric SAR for discriminating the surface coverage. The work is intended to furnish a guideline to develop an optimal strategy for acquiring and processing polarimetric data to be used for land classification

Plasma levels of leptin and mammographic density among postmenopausal women: a cross-sectional study

INTRODUCTION: Obesity has been linked to increased risk of breast cancer in postmenopausal women. Increased peripheral production of estrogens has been regarded as the main cause for this association, but other features of increased body fat mass may also play a part. Leptin is a protein produced mainly by adipose tissue and may represent a growth factor in cancer. We examined the association between leptin plasma levels and mammographic density, a biomarker for breast cancer risk. METHODS: We included data from postmenopausal women aged 55 and older, who participated in a cross-sectional mammography study in Tromsø, Norway. Mammograms, plasma leptin measurements as well as information on anthropometric and hormonal/reproductive factors were available from 967 women. We assessed mammographic density using a previously validated computer-assisted method. Multiple linear regression analysis was applied to investigate the association between mammographic density and quartiles of plasma leptin concentration. Because we hypothesized that the effect of leptin on mammographic density could vary depending on the amount of nondense or fat tissue in the breast, we also performed analyses on plasma leptin levels and mammographic density within tertiles of mammographic nondense area. RESULTS: After adjusting for age, postmenopausal hormone use, number of full-term pregnancies and age of first birth, there was an inverse association between leptin and absolute mammographic density (P(trend )= 0.001). When we additionally adjusted for body mass index and mammographic nondense area, no statistically significant association between plasma leptin and mammographic density was found (P(trend )= 0.16). Stratified analyses suggested that the association between plasma leptin and mammographic density could differ with the amount of nondense area of the mammogram, with the strongest association between leptin and mammographic absolute density in the stratum with the medium breast fat content (P(trend )= 0.003, P for interaction = 0.05). CONCLUSION: We found no overall consistent association between the plasma concentration of leptin and absolute mammographic density. Although weak, there was some suggestion that the association between leptin and mammographic density could differ with the amount of fat tissue in the breast

Ground-based remote sensing of wind, temperature and aerosol backscattering in an urban environment during different atmospheric stability conditions

The diurnal evolution of the urban boundary layer over the central area of Rome was observed by the simultaneous and co-located operation of a Doppler sodar, a microwave radiometer and a dual polarization lidar. The Doppler sodar was configured to provide a wind profile up to about 800 m, and a time-height picture of the thermal structure of the urban boundary layer. A microwave radiometer provided a temperature profile up to 600 m with a height resolution of 50 m. The lidar provided profiles of the aerosol backscattering up to about 7-10 km with 30 m height resolution. The experiment was conducted for several days in the year 1998 during day and night with clear sky and low wind. The aerosol profiles in the urban troposphere appear linked to stability conditions in the lower layers and strong pollution. The presence of aerosols, typically in the afternoon hours at heights up to 2-3 km, can be related to a relatively high mixed layer. Such layer is caused by free convection as indicated by the Richardson number, estimated by the temperature and wind data. Some typical case studies are discussed. (C) 2001 Elsevier Science Ltd. All rights reserved

A Physical–Statistical Approach to Match Passive Microwave Retrieval of Rainfall to Mediterranean Climatology

A physical-statistical approach to simulate cloud structures and their upward radiation over the Mediterranean is described. It aims to construct a synthetic database of microwave passive observations matching the climatological conditions of this geographical region. The synthetic database is conceived to train a Bayesian maximum a postetioti probability inversion scheme to retrieve precipitating cloud parameters from spaceborne microwave radiometric data. The initial microphysical a priori information on vertical profiles of cloud parameters is derived from a mesoscale cloud-resolving model. In order to complement information from cloud models and to match simulations to the conditions of the area of interest, a new approach is proposed. Climatological constraints over the Mediterranean are derived on a monthly basis from available radiosounding profiles, rain-gauge network measurements, and colocated METEOSAT infrared measurements. In order to introduce the actual surface background in the radiative-transfer simulations, a further constraint is represented by the monthly average and variance maps of surface emissivity derived from Special Sensor Microwave Imager (SSM/I) clear-air observations. A validation of the forward model is carried out by comparing a large set of brightness temperatures measured by the SSM/I with the synthetic cloud radiative database to asses its representativeness and range of variability. The marginal contribution of each constraint source, used in the matching process, is also evaluated. Finally, surface rain rates, retrieved from SSM/I data using the new synthetic database, are compared with colocated rain rates measured by a rain-gauge network along the Tiber River basin in Italy throughout 1995. This comparison is performed both for selected case studies and in a statistical way, discussing the major advantages and limitations of the proposed approach

A Dynamic Culture Method to Produce Ovarian Cancer Spheroids under Physiologically-Relevant Shear Stress

The transcoelomic metastasis pathway is an alternative to traditional lymphatic/hematogenic metastasis. It is most frequently observed in ovarian cancer, though it has been documented in colon and gastric cancers as well. In transcoelomic metastasis, primary tumor cells are released into the abdominal cavity and form cell aggregates known as spheroids. These spheroids travel through the peritoneal fluid and implant at secondary sites, leading to the formation of new tumor lesions in the peritoneal lining and the organs in the cavity. Models of this process that incorporate the fluid shear stress (FSS) experienced by these spheroids are few, and most have not been fully characterized. Proposed herein is the adaption of a known dynamic cell culture system, the orbital shaker, to create an environment with physiologically-relevant FSS for spheroid formation. Experimental conditions (rotation speed, well size and cell density) were optimized to achieve physiologically-relevant FSS while facilitating the formation of spheroids that are also of a physiologically-relevant size. The FSS improves the roundness and size consistency of spheroids versus equivalent static methods and are even comparable to established high-throughput arrays, while maintaining nearly equivalent viability. This effect was seen in both highly metastatic and modestly metastatic cell lines. The spheroids generated using this technique were fully amenable to functional assays and will allow for better characterization of FSS’s effects on metastatic behavior and serve as a drug screening platform. This model can also be built upon in the future by adding more aspects of the peritoneal microenvironment, further enhancing its in vivo relevance