MULTI TIMES IMAGES FUSION BASED ON WAVELET THEORY

The development of new monitoring systems and the increasing interest of researchers in obtaining reliable measurements have leaded to the development of automatic monitoring moving objects. One way to ensure monitoring object is to use multi time's image fusion. Image fusion is a sub area of the more general topic of data fusion. Image fusion can be roughly defined as the process of combining multiple input images into an image, which contains the "relevant" information from the inputs. The aim of image fusion is to integrate complementary and redundant information from multiple images to create a composite that contains a better fused image than any of the individual source images. Main purpose of the former is to increase both the spectral and spatial resolution of images by combining multiple images. In this paper we tried to use this theory for moving object tracking, so with the usage of multi images that are obtained in different times and combination of them with this theory we identify the path of movement of moving object so this result could help us to implement automatic systems that that could monitor objects automatically without human interventation. So in this paper first we will discuss the principal of fusion and its famous method (wavelet theory) and all process that involved for doing a fusion process

Size-dependent effects of microplastic on uptake, immune system, related gene expression and histopathology of goldfish (Carassius auratus)

Todays, with the industrialization of human societies, pollution of aquatic ecosystems with plastics derivatives are a serious concern, affecting the life of their organisms. The present study was conducted to investigate the size effects of micro-plastic, polystyrene on some physiological lesions of the goldfish, Carassius auratus. Fish were exposed to two sizes (0.25 and 8 μm) polystyrene at different environmentally relevant concentrations. The exposure trial was done in two steps. First, fish exposed to a stable concentration of 300 mg/L polystyrene for 168 h. Gill, intestine, and liver tissues were sampled every 24 h to investigate the accumulation of polystyrene. Then, fish were exposed in three replicates to 0 (control), 0.05, 0.5, and 5 mg/L polystyrene in two sizes of 0.25 and 8 μm for 28 days. After the exposure period, gill, liver, and intestine tissues were sampled for histological study, also, serum samples were collected for biochemical assays. Fluorescent microscope observations confirmed the accumulation of polystyrene in tissue samples with time. In addition, histological lesions were found in the liver, intestine, and gill of the exposed fish. The severity of lesions showed a size and dose-dependent pattern. Polystyrene induced the antioxidant system of exposed fish through elevating the levels of SOD and CAT activity and significant difference in expression of antioxidant related genes (CAT, SOD and HSP70). In conclusion, the results of the present study confirmed the toxic effects of microplastic, polystyrene on goldfish. © 2021 Elsevier Lt

Emergent spectral properties of river network topology: an optimal channel network approach

Abstract Characterization of river drainage networks has been a subject of research for many years. However, most previous studies have been limited to quantities which are loosely connected to the topological properties of these networks. In this work, through a graph-theoretic formulation of drainage river networks, we investigate the eigenvalue spectra of their adjacency matrix. First, we introduce a graph theory model for river networks and explore the properties of the network through its adjacency matrix. Next, we show that the eigenvalue spectra of such complex networks follow distinct patterns and exhibit striking features including a spectral gap in which no eigenvalue exists as well as a finite number of zero eigenvalues. We show that such spectral features are closely related to the branching topology of the associated river networks. In this regard, we find an empirical relation for the spectral gap and nullity in terms of the energy dissipation exponent of the drainage networks. In addition, the eigenvalue distribution is found to follow a finite-width probability density function with certain skewness which is related to the drainage pattern. Our results are based on optimal channel network simulations and validated through examples obtained from physical experiments on landscape evolution. These results suggest the potential of the spectral graph techniques in characterizing and modeling river networks