A deterministic descriptive regularization-based method for SAR tomography in urban areas

In recent years, Synthetic Aperture Radar (SAR) Tomography (TomoSAR) has ascertained great potential for the three-dimensional (3-D) reconstruction of observed scenes, especially in urban areas. However, the number of proceed snapshots (observations) is usually less than that of slant height samples (unknowns) in TomoSAR inversion processes. This impairs the quality of the reconstructed vertical information. To cope with this issue and improve the reliability of reconstructed vertical information, this paper investigates the possible potential of a deterministic descriptive regularization-based method. Deterministic descriptive regularization is a well-conditioned optimization framework based on the descriptive idea of a regularization solution. This strategy can help to mitigate the effect of the ill-posed problem. Thus, it can assist SAR tomography to deal with the possible impairing issues arising from low numbers and the distribution of baselines. For this purpose, the result of the proposed strategy is compared with the outcomes from the standard TomoSAR techniques, including Beamforming, Capon, and Minimum Norm. The proposed method for reconstruction of the reflectivity function of the observed scene has been performed on a dataset acquired by the Sentinel-1 sensor in 2022 over Tehran City, Iran. The experimental results indicate that the proposed algorithm can estimate building heights with a vertical accuracy of better than 91%. These results demonstrate the great potential of the proposed method for reconstructing the full 3-D images of urban area

Evaluation of nonparametric SAR tomography methods for urban building reconstruction

Recently, the synthetic aperture radar tomography (TomoSAR) technique has attracted significant attention owing to its 3-D reconstruction capability of complex urban environments. The availability of a high number of images is usually a requirement for nonparametric spectral estimation methods. This letter evaluates the potential of four nonparametric spectral estimation algorithms, that is: 1) linear prediction (LP); 2) minimum norm (MN); 3) singular value decomposition (SVD); and 4) Capon for improved tomographic reconstruction of the third dimension of built-up areas with a small number of observations. The performance analysis is carried out for both simulated and real SAR datasets. The returns from the employed techniques indicate the efficient and low-computational estimator of LP by minimizing the average output signal power at the array of antenna elements and make it possible to separate multiple scatters at a distance below the Rayleigh resolution and clean sidelobes’ phenomena in the elevation profiles. The experimental results of a dataset acquired by the TerraSAR-X sensor verify the effectiveness of the LP spectral estimator algorithm in the reconstruction of urban buildings. The estimated height of scatterers with the LP method is considerably similar to the ground-observed data

Effects of nano-clay on biological resistance of wood-plastic composite against five wood-deteriorating fungi

Effects of nano-clay on weight loss of wood-plastic composites (WPC) by five fungi were studied. Nanoclay particles of 20 to 50 nm size were applied at 2, 4, and 6% WPC of 0,90 g/cm3 density. The white-rot fungi Physisporinus vitreus, Pleurotus ostreatus and Trametes versicolor as well as the brown-rot species Antrodia vaillantii and Coniophora puteana were used. Mass loss tests were conducted according to the European standard. The highest (3.2%) and lowest (0,2%) mass losses were produced by T. versicolor and P. vitreus in the control and 6%-nanoclay treatments, respectively. Obviously the weight loss of WPC depends on the fungus species. Although weight losses were extremely low, nano-clay considerably inhibited the growth of wood-deteriorating fungi. Mass loss correlated with water absorption

Investigation of the Accidents Recorded at an Emergency Management Center Using the Pareto Chart: A Cross-Sectional Study in Gonabad, Iran, During 2014-2016

Background: This study investigated the accidents recorded at the Gonabad Hospital Management Center for Hospital Management from 2014 to 2016, and identified important causes or parameters that influenced the incidence of accidents using the Pareto chart. Materials and Methods: This descriptive and analytic study examined 25,414 incidents recorded at the Gonabad Hospital Management Center. The key variables such as the types of accident, age, time, types of lesion, and treatment, were collected for transport and non-transport accident. Data analysis was performed using Pareto chart as well as Minitabver v.16 and SPSS v.21 software. Results: Based on the results, the highest rate of the accidents (39.79%) were among people aged between 0-10 years. Transport accidents (17.61%) and heart attacks (10.92%) were the most common that occurred during the study. The spring had the highest rate of accidents, while the winter had the lowest. Conclusion: Transportation accidents had the highest rate of incidents and injuries; therefore, the safety of transportation and vehicles should be taken more seriously

Studying the Polypropylenimine-G2 (PPI-G2) Dendrimer Performance in Removal of Escherichia coli, Proteus mirabilis, Bacillus subtilis and Staphylococcus aureus from Aqueous Solution

Abstract Background: Dendrimers are a subset of branched structures that have certain structural order. The aim of this study was to investigate the performance of Polypropylenimine-G2 (PPI-G2) dendrimers in removal of Escherichia coli, Proteus mirabilis, Bacillus subtilis and Staphylococcus aureus from aqueous solution. Materials and Methods: In this experimental study, initially dilution of 103 CFU/ml was prepared from each strain of bacteria. Then, different concentrations of dendrimers (0.5, 5, 50 and 500 µg/ml) was added to water. In order to determine the efficiency of dendrimers in removal of bacteria, samples were taken at different times (0, 10, 20, 30, 40, 50 and 60 min) and were cultured on nutrient agar medium. Samples were incubated for 24 hours at 37 ° C and then the number of colonies was counted. Results: By the increasment of dendrimer concentration and contact time, the number of bacteria in aqueous solution decreased. In times of 40, 50 and 60 minutes, and the concentrations of 50 and 500 µg/ml, all kinds of bacteria in aqueous solution were removed. 0.5 µg/ml of dendrimer concentration had not effect in reducing the number of Escherichia coli and Proteus mirabilis. The effect of dendrimer on gram-negative bacteria was weaker than gram-positive bacteria. Conclusion: Results of this study indicated that PPI-G2 dendrimer is able to remove Escherichia coli, Proteus mirabilis, Staphylococcus aureus and Bacillus subtilis in aqueous solution. However, using dendrimers can be considered as a new approach for drinking water disinfection but it requires further wide range studies