Sub Pixel Classification Analysis for Hyperspectral Data (Hyperion) for Cairo Region, Egypt

Traditional hard classifiers in remote sensing applications can label image pixels only with one class, so landcover (e.g. trees) can only be recorded as either present or absent. This approach might lead to inaccurate imageclassification and accordingly inaccurate land cover. The proposed analysis technique provides the relativeabundance of surface materials and the context within a pixel that may be a potential solution to effectivelyidentifying the land-cover distribution. This research is applied on the central region of Cairo using hyperspectralimage data, which provides a large amount of spectral information. A spectral mixture analysis approach is usedon Hyperion data (hyperspectral data) to produce abundance images representing the percentage of the existenceof each material/land cover with a pixel. The uniqueness of this study comes from the fact that it is the first timeHyperion data has been used to extract land cover in Egypt.Keywords: Spectral Mixture Analysis, Hyperspectral Data, Hyperion Data, Cairo, Egyp

A Developed Algorithm for Automating the Multiple Bands Multiple Endmember Selection of Hyperion data Applied on Central of Cairo, Egypt

This study attempts to provide an answer regarding the utility of Hyperion imagery in mapping urban settings in developed countries. The authors present a novel method for extracting quantitative land cover information at the sub-pixel level from hyperspectral or Hyperion imagery. The proposed method is based on the multiple endmember spectral mixture (MESMA) proposed by Roberts et al. (1998b), but extends it to handle the high-dimensional pixels characterizing hyperspectral images. The proposed method utilizes a multiband multiple endmember spectral mixture analysis (Multiband MESMA) model that allows for both spectral bands and endmembers to vary on a per-pixel basis across a hyperspectral image. The goal is to select an optimal subset of spectral bands that maximizes spectral separability among a candidate set of endmembers for a given pixel, and accordingly to minimize spectral confusion among modeled endmembers and increase the accuracy and physical representativeness of derived fractions for that pixel. The authors develop a tool to automate this method and test its utility in a case study using a Hyperion image of Central Cairo, Egypt. The EO-1 Hyperion hyperspectral sensor is the only source of hyperspectral data currently available for Cairo, unlike cities in Europe and North America, where multiple sources of such data generally exist. The study scene represents a very heterogeneous landscape and has an ecological footprint of a complex range of interrelated socioeconomic, environmental and urban dynamics. The results of this study show that Hyperion data, with its rich spectral information, can help address some of the limitations in automated mapping that are reported by previous studies. For this, proper bands and endmembers are selected and used within a multiple endmember, with a multiple-band SMA process to determine the best Root Mean Square Error (RMSE) and abundance percentages. This results in a better mapping of land cover extricated from hyperspectral imagery (Hyperion). Keywords: Spectral Mixture Analysis, Hyperspectral Data, Hyperion Data, Cairo, Egyp

The role of antioxidants and zinc in minimal hepatic encephalopathy: a randomized trial

Background: Minimal hepatic encephalopathy (MHE) has a far-reaching impact on quality and function ability in daily life and may progress to overt hepatic encephalopathy. There is a synergistic effect between systemic oxidative stress and ammonia that is implicated in the pathogenesis of hepatic encephalopathy. The aim of this study is to investigate the effectiveness of oral supplementation of antioxidants and zinc gluconate on MHE versus lactulose. Methods: Our study included 58 patients with cirrhosis diagnosed as having MHE by neuropsychometric tests, including number connection test part A (NCT-A), digit symbol test (DST) and block design tests (BDTs). Patients were randomized to receive 175 mg zinc gluconate, 50,000 IU vitamin A, 500 mg vitamin C and 100 mg vitamin E once daily plus lactulose, dose 30–60 ml/day for 3 months [group A ( n = 31)] or initiated and maintained on lactulose dose 30–60 ml/day for 3 months [group B ( n = 27)]. Neuropsychometric tests and laboratory investigations were repeated after 3 months of therapy. Results: Compared with the baseline neuropsychometric tests, a significant improvement was reported in patients with MHE after 3 months of antioxidant and zinc therapy (group A) versus patients with lactulose therapy (group B) (NCT-A, p < 0.001; DST, p = 0.006; BDT, p < 0.001). Antioxidant and zinc supplementation significantly decreased arterial ammonia level, alanine aminotransferase (ALT), aspartate aminotransferase (AST) ( p < 0.001) and improved Child–Pugh score in MHE after 3 months of therapy ( p = 0.024). Conclusion: Antioxidant and zinc supplementation can improve MHE in patients with liver cirrhosis

A risk score to predict 30-day hospital readmission rate in cirrhotic patients with spontaneous bacterial peritonitis

Abstract Background and aim There is lack of 30-day hospital readmission prediction score in patients with liver cirrhosis and SBP. The aim of this study is to recognize factors capable of predicting 30-day readmission and to develop a readmission risk score in patients with SBP. Methods This study prospectively examined the 30-day hospital readmission for patients previously discharged with a diagnosis of SBP. Based on index hospitalization variables, a multivariable logistic regression model was implemented to recognize predictors of patient hospital readmission within 30 days. Consequently, Mousa readmission risk score was established to predict 30-day hospital readmission. Results Of 475 patients hospitalized with SBP, 400 patients were included in this study. The 30-day readmission rate was 26.5%, with 16.03% of patients readmitted with SBP. Age ≥ 60, MELD > 15, serum bilirubin > 1.5 mg/dL, creatinine > 1.2 mg/dL, INR > 1.4, albumin < 2.5 g/dL, platelets count ≤ 74 (103/dL) were found to be independent predictors of 30-day readmission. Incorporating these predictors, Mousa readmission score was established to predict 30-day patient readmissions. ROC curve analysis demonstrated that at a cutoff value ≥ 4, Mousa score had optimum discriminative power for predicting the readmission in SBP with sensitivity 90.6% and specificity 92.9%. However, at cutoff value ≥ 6 the sensitivity and specificity were 77.4% and 99.7%, respectively, while a cutoff value ≥ 2 had sensitivity of 99.1% and specificity of 31.6%. Conclusions The 30-day readmission rate of SBP was 25.6%. With the suggested simple risk assessment Mousa score, patients at high risk for early readmission can be easily identified so as to possibly prevent poorer outcomes