Ensemble-based clustering of large probabilistic graphs using neighborhood and distance metric learning

Graphs are commonly used to express the communication of various data. Faced with uncertain data, we have probabilistic graphs. As a fundamental problem of such graphs, clustering has many applications in analyzing uncertain data. In this paper, we propose a novel method based on ensemble clustering for large probabilistic graphs. To generate ensemble clusters, we develop a set of probable possible worlds of the initial probabilistic graph. Then, we present a probabilistic co-association matrix as a consensus function to integrate base clustering results. It relies on co-occurrences of node pairs based on the probability of the corresponding common cluster graphs. Also, we apply two improvements in the steps before and after of ensembles generation. In the before step, we append neighborhood information based on node features to the initial graph to achieve a more accurate estimation of the probability between the nodes. In the after step, we use supervised metric learning-based Mahalanobis distance to automatically learn a metric from ensemble clusters. It aims to gain crucial features of the base clustering results. We evaluate our work using five real-world datasets and three clustering evaluation metrics, namely the Dunn index, Davies–Bouldin index, and Silhouette coefficient. The results show the impressive performance of clustering large probabilistic graphs.

     

Effects of Glow-Discharge Parameters on Silicon Coating Thickness Deposited on 316 Stainless Steel Samples

Silicon as a light element can be used as the tokamak first wall coating in order to protect the plasma from impurities which come from the wall. In this paper, we deposit an amorphous-silicon layer by the use of the glow discharge technique on the wall surface of the test chamber made from SS316. To do so, we employ silane as a source of silicon ions. The siliconization process is conducted at two time durations of 90 and 150 min. SEM image of the coated surface shows that the structure of the coated layer deposited by the 150-min is more compact in comparison with that of 90-min. Effect of current density on coating properties is evaluated by placing four samples at different locations on the wall surface which shows that the optimal values of current density are in the range of 14–20 μA/cm² and the higher range of current density can damage the coating. The results confirm that by increasing the time of siliconization the coating thickness is increased successfully from 100 to 250 nm without appearance of any damage in coating.     

Identification of B-Cell Epitopes for Eliciting Neutralizing Antibodies against the SARS-CoV-2 Spike Protein through Bioinformatics and Monoclonal Antibody Targeting

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global public health crisis. Effective COVID-19 vaccines developed by Pfizer-BioNTech, Moderna, and Astra Zeneca have made significant impacts in controlling the COVID-19 burden, especially in reducing the transmission of SARS-CoV-2 and hospitalization incidences. In view of the emergence of new SARS-CoV-2 variants, vaccines developed against the Wuhan strain were less effective against the variants. Neutralizing antibodies produced by B cells are a critical component of adaptive immunity, particularly in neutralizing viruses by blocking virus attachment and entry into cells. Therefore, the identification of protective linear B-cell epitopes can guide epitope-based peptide designs. This study reviews the identification of SARS-CoV-2 B-cell epitopes within the spike, membrane and nucleocapsid proteins that can be incorporated as potent B-cell epitopes into peptide vaccine constructs. The bioinformatic approach offers a new in silico strategy for the mapping and identification of potential B-cell epitopes and, upon in vivo validation, would be useful for the rapid development of effective multi-epitope-based vaccines. Potent B-cell epitopes were identified from the analysis of three-dimensional structures of monoclonal antibodies in a complex with SARS-CoV-2 from literature mining. This review provides significant insights into the elicitation of potential neutralizing antibodies by potent B-cell epitopes, which could advance the development of multi-epitope peptide vaccines against SARS-CoV-2.     

Polyunsaturated Fatty Acids and Modulation of Cholesterol Homeostasis in THP-1 Macrophage-Derived Foam Cells

Transformation of macrophages to foam cells is determined by the rates of cholesterol uptake and efflux. This study uses a real time RT-PCR technique to investigate the role of conjugated linoleic acid (CLA), α-linolenic acid (ALA) and eicosapentaenoic acid (EPA) in the regulation of the ATP-binding cassette A1 (ABCA1) and liver X receptor α (LXR) genes, which are involved in cholesterol homeostasis. Accordingly, these fatty acids significantly reduced the total, free and esterified cholesterols within the foam cells. While the expression of the ABCA1 and LXRα genes was increased in the presence of the pharmacological LXRα ligand, T0901317, their mRNA expression was not significantly affected by CLA, ALA and EPA. These results suggest that although polyunsaturated fatty acids have an effect on cholesterol homeostasis, they cannot change the expression of the ABCA1 and LXRα genes. Alternatively, several other genes and proteins may be involved.     

Sol–gel synthesis of silicon carbide on silicon pyramids: a promising candidate for supercapacitor electrodes

In this study, Si porous pyramids nanostructures were synthesized by the metal-assisted chemical etching technique. Different KOH concentrations were used to develop high surface area Si porous pyramids for application as supercapacitor electrodes. Field-emission scanning electron microscope (FE-SEM) studies showed that 5% KOH solution will lead to high surface area Si pyramids with a specific capacitance of 90.3 F/cm². Silicon carbide (SiC) thin film was coated on Si pyramids (SiC@Si) using a facile sol–gel method followed by a carbothermal reduction process. Tetraethylorthosilicate and sugar were used as carbon sources. X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR) and FE-SEM analysis were used to characterize the developed SiC@Si samples. The developed SiC@ Si electrode exhibited a high specific capacitance of 135.5 F/cm² at a scan rate of 10 mV/s (in 1 M NaOH electrolyte). The supercapacitor capability of this SiC@Si structure is significantly higher than classical materials. Because of its facile, controllable and efficient synthesis technique, this novel SiC@Si can be considered a very promising candidate for power sources applications.

     

Rheological properties of endodontic sealers: the effect of time, temperature, and composition

This study was aimed to investigate the effect of different parameters such as shear rate, temperature, and time on the viscosity of four endodontic sealers. Furthermore, the effect of variations in powder to liquid ratio of two powder/liquid sealers upon their viscosity was evaluated. The tested sealers were AH Plus, Endofill, AH 26, and Epiphany self-etch (SE) sealer. As all of the tested sealers contain particles of resinous composites; shear thinning and some time-dependency of viscosity are expected. Therefore, steady shear viscosity and thixotropy behavior were assessed. The samples were examined at 25 and 37?°C with the shear rate ranged from 0.0001 to 100?s^?1. All sealers almost exhibited shear thinning behavior. At both temperatures of 25 and 37?°C, the viscosities of sealers were at the same order and ranked from the highest to the lowest as follows: Epiphany SE, AH Plus, AH 26, and Endofill. The samples with higher powder to liquid ratio of 3:1 exhibited higher viscosity compared to 2:1 ratio in both tested temperatures. With the exception of Epiphany SE and AH 26 (at shear rate less than 1?s^?1), viscosity of all sealers decreased with increasing temperature from 25 to 37?°C. All sealers exhibited time-dependent viscosity characteristics at the two examined temperatures.     

Heart Sound Localization in Respiratory Sounds Based on Singular Spectrum Analysis and Frequency Features

Heart sounds are the main obstacle in lung sound analysis. To tackle this obstacle, we propose a diagnosis algorithm that uses singular spectrum analysis (SSA) and frequency features of heart and lung sounds. In particular, we introduce a frequency coefficient that shows the frequency difference between heart and lung sounds. The proposed algorithm is applied to a synthetic mixture of heart and lung sounds. The results show that heart sounds can be extracted successfully and localizations for the first and second heart sounds are remarkably performed. An error analysis of the localization results shows that the proposed algorithm has fewer errors compared to the SSA method, which is one of the most powerful methods in the localization of heart sounds. The presented algorithm is also applied in the cases of recorded respiratory sounds from the chest walls of five healthy subjects. The efficiency of the algorithm in extracting heart sounds from the recorded breathing sounds is verified with power spectral density evaluations and listening. Most studies have used only normal respiratory sounds, whereas we additionally use abnormal breathing sounds to validate the strength of our achievements.     

The Determination of Average Stability Constant of NickeI-FA Complex at pH = 8,0 by the Solubility Method

At pH = 8, the complex formation process of Ni（Ⅱ） ions with FA was studied by the solubility method. FA were separated from the river Mtkvari by the adsorption-chromotographic method. The charcoal （BAU, Russia） was used as a sorbent. The old suspension of Ni（Ⅱ） hydroxide was used as the solid phase, on which was added the increasing quantity of standard solution of FA. In diluted solutions, at pH = 8.0 the dominant form of Ni（Ⅱ） is nickel dihydroxocomplex Ni（OH）2^0. It was established that in the Ni（OH）2（solid）-Ni（OH）2^0（solution）-FA2-H20 system dominates nickel dyhydroxofulvate complex with the structure 1：1, [Ni（OH）2FA]2-. The average stability constant of nickel dyhydroxofulvate complex was calculated based on experimental data flNi（OH）2FA2＂ = 5.3 × 105.     

Effect of Radiation on Mixed Convection Inside a Lid-Driven Square Cavity With Various Optical Thicknesses and Richardson Numbers

This work studies numerically the effect of the radiative heat transfer on the flow and thermal behaviors of the mixed convection in a lid-driven square cavity in the presence of radiatively emitting, absorbing, and isotropically scattering gray medium. The Boussinesq approximation has been used in modeling the governing equations, and the SIMPLE (semi-implicit method for pressure-linked equations) algorithm is used in coupling the velocity and pressure fields. The radiative transfer equation and the governing equations have been solved respectively by the discrete ordinates method and the finite-volume method in order to obtain the temperature, velocity, and heat flux distributions in the participating medium. The present numerical simulations are validated by comparison with several earlier studies. Then, the temperature and velocity distributions and Nusselt numbers have been analyzed in a broad range of optical thicknesses from 0 to 100 and Richardson numbers from 0.01 to 100. The results show that the radiation has a significant role on the flow and thermal behaviors in the lid-driven square cavity. As an example, we can refer to a sweep behavior that is detected in the velocity distributions of the lid-driven cavity.