Diagnosis of liver disease by computer- assisted imaging techniques: A literature review

Copyright © 2022 The authors. Diagnosis of liver disease using computer-aided detection (CAD) systems is one of the most efficient and cost-effective methods of medical image diagnosis. Accurate disease detection by using ultrasound images or other medical imaging modalities depends on the physician's or doctor's experience and skill. CAD systems have a critical role in helping experts make accurate and right-sized assessments. There are different types of CAD systems for diagnosing different diseases, and one of the applications is in liver disease diagnosis and detection by using intelligent algorithms to detect any abnormalities. Machine learning and deep learning algorithms and models play also a big role in this area. In this article, we tried to review the techniques which are utilized in different stages of CAD systems and pursue the methods used in preprocessing, extracting, and selecting features and classification. Also, different techniques are used to segment and analyze the liver ultrasound medical images, which is still a challenging approach to how to use these techniques and their technical and clinical effectiveness as a global approach

An integrated study of earth resources in the state of California using remote sensing techniques

There are no author-identified significant results in this report

Level Crossing Analysis of Growing surfaces

We investigate the average frequency of positive slope $\nu_{\alpha}^{+}$, crossing the height $\alpha = h- \bar h$ in the surface growing processes. The exact level crossing analysis of the random deposition model and the Kardar-Parisi-Zhang equation in the strong coupling limit before creation of singularities are given.Comment: 5 pages, two column, latex, three figure

An integrated study of earth resources in the state of California using remote sensing techniques, volume 2

There are no author-identified significant results in this report

Modification of immobilized titanium dioxide nanostructures by argon plasma for photocatalytic removal of organic dyes

The aim of this study was to modify surface properties of immobilized rutile TiO 2 using Argon cold plasma treatment and to evaluate the performance of the catalyst in photocatalytic elimination of synthetic dyes in UV/TiO 2 /H 2 O 2 process. The surface-modified TiO 2 was characterized by XRD, EDX, SEM, UV-DRS and XPS analyses. Response surface methodology was adopted to achieve high catalyst efficiency by evaluating the effect of two main independent cold plasma treatment parameters (exposure time and pressure) on surface modification of the catalyst. The increase of the plasma operation pressure led to higher decolorization percentage, while the increase of plasma exposure time decreased the decolorization efficiency. RSM methodology predicted optimum plasma treatment conditions to be 0.78 Torr and 21 min of exposure time, which resulted in decolorization of 10 mg/L solution of the malachite green solution by 94.94 in 30 min. The plasma treatment decreased the oxygen to titanium ratio and caused oxygen vacancy on the surface of the catalyst, resulting in the superior performance of the plasma-treated catalyst. Pseudo first-order kinetic rate constant for the plasma-treated catalyst was 4.28 and 2.03 times higher than the rate constant for the non-treated photocatalyst in decolorization of aqueous solutions of malachite green and crystal violet, respectively. © 2019 by the authors

Inflammation Response of Water-Soluble Fractions in Atmospheric Fine Particulates: A Seasonal Observation in 10 Large Chinese Cities

Spatiotemporal trends in pro-inflammatory (interleukin (IL)-6 and IL-8) release after exposure to the water-soluble fractions of PM2.5 sampled in 10 large Chinese cities over 1 year were investigated. Chemical components (water-soluble ions, metal(loid) elements, water-soluble organic carbon (WSOC), humic-like substances (HULIS), and endotoxins) in PM2.5 samples were measured, and the molecular structure of WSOC was also analyzed by nuclear magnetic resonance. Changes in DNA methylation and gene expression of candidate genes were also evaluated to explore the potential mechanisms. PM2.5 from southern cities induced lower pro-inflammatory responses compared to those from northern cities. Seasonal differences in toxicity were noted among the cities. IL-6 was significantly correlated with HULIS (as the main fraction of WSOC with oxygenated carbohydrate structures characteristic), Pb, and endotoxin. Furthermore, DNA methylation and gene expression changes in RASSF2 and CYPIB1 were related to pro inflammatory secretion. Certain components of PM25, rather than PM2.5 mass itself, determine the pro-inflammatory release. In particular, HULIS, which originated from primary biomass burning and residual coal combustion, and secondary organic aerosols, appear to be the key component in PM2.5 to induce human health risk

Markov Properties of Electrical Discharge Current Fluctuations in Plasma

Using the Markovian method, we study the stochastic nature of electrical discharge current fluctuations in the Helium plasma. Sinusoidal trends are extracted from the data set by the Fourier-Detrended Fluctuation analysis and consequently cleaned data is retrieved. We determine the Markov time scale of the detrended data set by using likelihood analysis. We also estimate the Kramers-Moyal's coefficients of the discharge current fluctuations and derive the corresponding Fokker-Planck equation. In addition, the obtained Langevin equation enables us to reconstruct discharge time series with similar statistical properties compared with the observed in the experiment. We also provide an exact decomposition of temporal correlation function by using Kramers-Moyal's coefficients. We show that for the stationary time series, the two point temporal correlation function has an exponential decaying behavior with a characteristic correlation time scale. Our results confirm that, there is no definite relation between correlation and Markov time scales. However both of them behave as monotonic increasing function of discharge current intensity. Finally to complete our analysis, the multifractal behavior of reconstructed time series using its Keramers-Moyal's coefficients and original data set are investigated. Extended self similarity analysis demonstrates that fluctuations in our experimental setup deviates from Kolmogorov (K41) theory for fully developed turbulence regime.Comment: 25 pages, 9 figures and 4 tables. V3: Added comments, references, figures and major correction

Iranome: A catalogue of genomic variations in the Iranian population

Considering the application of human genome variation databases in precision medicine, population-specific genome projects are continuously being developed. However, the Middle Eastern population is underrepresented in current databases. Accordingly, we established Iranome database (www.iranome.com) by performing whole exome sequencing on 800 individuals from eight major Iranian ethnic groups representing the second largest population of Middle East. We identified 1,575,702 variants of which 308,311 were novel (19.6%). Also, by presenting higher frequency for 37,384 novel or known rare variants, Iranome database can improve the power of molecular diagnosis. Moreover, attainable clinical information makes this database a good resource for classifying pathogenicity of rare variants. Principal components analysis indicated that, apart from Iranian-Baluchs, Iranian-Turkmen, and Iranian-Persian Gulf Islanders, who form their own clusters, rest of the population were genetically linked, forming a super-population. Furthermore, only 0.6% of novel variants showed counterparts in "Greater Middle East Variome Project", emphasizing the value of Iranome at national level by releasing a comprehensive catalog of Iranian genomic variations and also filling another gap in the catalog of human genome variations at international level. We introduce Iranome as a resource which may also be applicable in other countries located in neighboring regions historically called Greater Iran (Persia)