Structural, photoluminescence, and optical characteristics of a Sm3+ -doped lead borate-strontium-tungsten glass system: Evaluation of Judd-Ofelt intensity parameters and radiative properties.

In this study, the melt quenching approach is used to synthesize a lead borate-strontium-based glass system doped with samarium ions. Modifications in the glass network structure arising from the addition of various concentrations of Sm3+ ions were investigated via Fourier transform infrared (FTIR) spectroscopy. FTIR analysis revealed B-O-B bridges, BO3 , and BO4 units are present. UV-vis-NIR spectroscopic measurement was performed to study the optical absorption spectra. Optical constants such as optical bandgap energies, refractive indices, and other related parameters were evaluated. The lifetime fluorescence decay was measured and ranged between 1.04 and 1.88 ns. The photoluminescence spectra in the range 500-750 nm revealed four transitions from the ground state 6 G5/2 to the excited states 6 H5/2 , 6 H7/2 , 6 H9/2 and 6 H11/2 and J-O theory was utilized to study these optical transitions for Sm3+ ions. Calculations of the oscillator strengths and J-O intensity parameters were performed and the obtained J-O parameters followed the sequence Ω4 > Ω6 > Ω2 . The ratio O/R indicated a high lattice asymmetry around the samarium ions. The values of lifetimes and branching ratios for the fabricated samples emphasized their suitability to be used in laser applications. The current glass samples are good candidates for orange and red emission devices.

A diagnostic genomic signal processing (GSP)-based system for automatic feature analysis and detection of COVID-19.

Coronavirus Disease 2019 (COVID-19) is a sudden viral contagion that appeared at the end of last year in Wuhan city, the Chinese province of Hubei, China. The fast spread of COVID-19 has led to a dangerous threat to worldwide health. Also in the last two decades, several viral epidemics have been listed like the severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002/2003, the influenza H1N1 in 2009 and recently the Middle East respiratory syndrome coronavirus (MERS-CoV) which appeared in Saudi Arabia in 2012. In this research, an automated system is created to differentiate between the COVID-19, SARS-CoV and MERS-CoV epidemics by using their genomic sequences recorded in the NCBI GenBank in order to facilitate the diagnosis process and increase the accuracy of disease detection in less time. The selected database contains 76 genes for each epidemic. Then, some features are extracted like a discrete Fourier transform (DFT), discrete cosine transform (DCT) and the seven moment invariants to two different classifiers. These classifiers are the k-nearest neighbor (KNN) algorithm and the trainable cascade-forward back propagation neural network where they give satisfying results to compare. To evaluate the performance of classifiers, there are some effective parameters calculated. They are accuracy (ACC), F1 score, error rate and Matthews correlation coefficient (MCC) that are 100%, 100%, 0 and 1, respectively, for the KNN algorithm and 98.89%, 98.34%, 0.0111 and 0.9754, respectively, for the cascade-forward network.

Development and multicenter validation of FIB-6: A novel, machine learning, simple bedside score to rule out liver cirrhosis and compensated advanced chronic liver disease in patients with chronic hepatitis C.

BACKGROUND: Non-invasive tests (NITs), such as Fibrosis-4 index (FIB-4) and the aspartate aminotransferase-to-platelet ratio index (APRI), developed using classical statistical methods, are increasingly used for determining liver fibrosis stages and recommended in treatment guidelines replacing the liver biopsy. Application of conventional cutoffs of FIB-4 and APRI resulted in high rates of misclassification of fibrosis stages. AIM: There is an unmet need for more accurate NITs that can overcome the limitations of FIB-4 and APRI. PATIENTS AND METHODS: Machine learning with the random forest algorithm was used to develop a non-invasive index using retrospective data of 7238 patients with biopsy-proven chronic hepatitis C from two centers in Egypt; derivation dataset (n = 1821) and validation set in the second center (n = 5417). Receiver operator curve analysis was used to define cutoffs for different stages of fibrosis. Performance of the new score was externally validated in cohorts from two other sites in Egypt (n = 560) and seven different countries (n = 1317). Fibrosis stages were determined using the METAVIR score. Results were also compared with three established tools (FIB-4, APRI, and the aspartate aminotransferase-to-alanine aminotransferase ratio [AAR]). RESULTS: Age in addition to readily available laboratory parameters such as aspartate, and alanine aminotransferases, alkaline phosphatase, albumin (g/dl), and platelet count (/cm3 ) correlated with the biopsy-derived stage of liver fibrosis in the derivation cohort and were used to construct the model for predicting the fibrosis stage by applying the random forest algorithm, resulting in an FIB-6 index, which can be calculated easily at http://fib6.elriah.info. Application of the cutoff values derived from the derivation group on the validation groups yielded very good performance in ruling out cirrhosis (negative predictive value [NPV] = 97.7%), compensated advance liver disease (NPV = 90.2%), and significant fibrosis (NPV = 65.7%). In the external validation groups from different countries, FIB-6 demonstrated higher sensitivity and NPV than FIB-4, APRI, and AAR. CONCLUSION: FIB-6 score is a non-invasive, simple, and accurate test for ruling out liver cirrhosis and compensated advance liver disease in patients with chronic hepatitis C and performs better than APRI, FIB-4, and AAR.

Investigation of Structural, Physical, and Attenuation Parameters of Glass: TeO2-Bi2O3-B2O3-TiO2-RE2O3 (RE: La, Ce, Sm, Er, and Yb), and Applications Thereof.

A novel series of glass, consisting of B2O3, Bi2O3, TeO2, and TiO2 (BBTT) containing rare earth oxide RE2O3, where RE is La, Ce, Sm, Er, and Yb, was prepared. We investigated the structural, optical, and gamma attenuation properties of the resultant glass. The optical energy bands, the linear refractive indices, the molar refractions, the metallization criteria, and the optical basicity were all determined for the prepared glass. Furthermore, physical parameters such as the density, the molar volume, the oxygen molar volume, and the oxygen packing density of the prepared glass, were computed. Both the values of density and optical energy of the prepared glass increased in the order of La2O3, Ce2O3, Sm2O3, Er2O3, and then Yb2O3. In addition, the glass doped with Yb2O3 had the lowest refractive index, electronic polarizability, and optical basicity values compared with the other prepared glass. The structures of the prepared glass were investigated by the deconvolution of infrared spectroscopy, which determined that TeO4, TeO3, BO4, BO3, BiO6, and TiO4 units had formed. Furthermore, the structural changes in glass are related to the ratio of the intensity of TeO4/TeO3, depending on the type of rare earth. It is also clarified that the resultant glass samples are good attenuators against low-energy radiation, especially those that modified by Yb2O3, which exhibited superior shielding efficiency at energies of 622, 1170, and 1330 keV. The optical and gamma ray spectroscopy results of the prepared glass show that it is a good candidate for nonlinear optical fibers, laser solid material, and optical shielding protection.

Investigation of Er3+ Ions Reinforced Zinc-Phosphate Glasses for Ionizing Radiation Shielding Applications.

Melt quenching technique is used for preparing glasses with chemical formula (70P2O5)-(16 - x)CdO-(14ZnO)-(xEr2O3), (x = 1-6 mol%). These glasses were named Er1, Er2, Er3, Er4, Er5, and Er6, respectively. Photon buildup factors, fast neutron absorption, and electron stopping of the prepared glasses were examined. Glasses' density was varied from 3.390 ± 0.003 for the Er1 glass sample to 3.412 ± 0.003 for the Er6 glass sample. The Buildup factor (BUF) spectra have relatively higher values in the Compton Scattering (CS) dominated areas compared to both Photoelectric effect (PE), and Pair Production (PP) dominated energy regions. The highest BUF appeared at the Er atom K-absorption edge, whose intensity increases as the molar concentration of Er2O3 in the glasses increases. The photon absorption efficiency (PAE) of the glasses increases according to the trend (PAE)Er1 < (PAE)Er2 < (PAE)Er3 < (PAE)Er4 < (PAE)Er5 < (PAE)Er6. Fast neutron removal cross-section, FNRC (ΣR) values of the glasses obtained via calculation varied from 0.1045-0.1039 cm-1 for Er1-Er6. Furthermore, the continuous slowing down approximation mode (CSDA) range enhances the kinetic energy of electrons for all glasses. Generally, results revealed that the investigated glasses could be applied for radiation shielding and dosimetric media.

UV-visible, Raman and E.S.R. studies of gamma-irradiated NiO-doped sodium metaphosphate glasses.

UV-visible spectroscopic measurements of Ni-doped sodium phosphate glasses were carried out before and after successive gamma irradiation. The undoped glass reveals strong UV absorption originating from trace iron impurities. NiO-doped glasses show characteristic absorption bands due mainly to octahedral coordination of Ni(2+) ions. Gamma irradiation produces induced bands generated from intrinsic defects and extrinsic defects. The changes in the spectroscopic data are discussed in relation to the structural evolution caused by the changes in composition and coordination state of nickel ions. The change in the growth behaviour of the induced bands is related to the annihilation or approach saturation of these characteristic induced bands. Raman and E.S.R. spectroscopic measurements confirm the presence of nickel as Ni(2+) ions in octahedral state.