Monitoring a labeled degree-corrected stochastic block model

The stochastic block model (SBM) is a random graph model that focuses on partitioning the nodes into blocks or communities. A degree-corrected stochastic block model (DCSBM) considers degree heterogeneity within nodes. Investigation of the type of edge label can be useful for studying networks. We have proposed a labeled degree-corrected stochastic block model (LDCSBM), added the probability of the occurrence of each edge label, and monitored the behavior of this network. The LDCSBM is a dynamic network that varies over time; thus, we applied the monitoring process to both the US Senate voting network and simulated networks by defining structural changes. We used the Shewhart control chart for detecting changes and studied the effect of Phase I parameter estimation on Phase II performance. The efficiency of the model for surveillance has been evaluated using the average run length for estimated parameters.     

Location-aware hazardous litter management for smart emergency governance in urban eco-cyber-physical systems

Multimedia Tools and Applications - Smart city management is facing a new challenge from littered face masks during COVID-19 pandemic. Addressing the issues of detection and collection of this...     

Modeling the Solubility of Carbon Dioxide and 1,1,1,2-Tetrafluoroethane in Ionic Liquids Using the van der Waals and Generic Redlich–Kwong Equations of State

Theoretical Foundations of Chemical Engineering - In this study, we have examined the modeling of gas solubility in twenty room temperature ionic liquids based on the van der Waals and generic...     

Preparation,characterization and in vitro biological response of simultaneous co-substitution of Zr+4/Sr+2 58S bioactive glass powder

In the present study, structure of zirconium-containing bioactive glass (58S-BG (Zr-BG)) with optimal fixed Zr content (5 mol.%) was modified by incorporation of strontium (Sr). These Zr and Sr-containing BGs (ZS-BGs) were synthesized by sol-gel method and substitution of Ca with modifier ions (Sr content = 0, 3, 6, 9, and 12 mol.%). The results obtained from characterization by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared (FTIR), and energy-dispersive X-ray spectroscopy (EDS) techniques from surface of all the ZS-BGs revealed formation of hydroxyapatite (HA) after 7 days of immersion in the simulated body fluid (SBF) solution. Evaluation of changes in the SBF solution, by monitoring pH variations and ions? concentration, was in agreement with the results of morphological and structural investigations. The in-vitro biological function of synthesized BGs was studied through (MTT) assay and alkaline phosphatase (ALP) activity analysis. The results showed that all the specimens significantly stimulated proliferation and viability of MC3T3 osteoblast-like cells. Furthermore, antibacterial studies confirmed less resistance of methicillin-resistant Staphylococcus aureus (MRSA) bacteria against ZS-BGs. Eventually, the results of in-vitro bio-analysis were clarified and confirmed by two cell staining techniques of Live/Dead and Dapi/Actin. This confirmation was achieved by observing the increased quantity of live cells and their nuclei as well as the decreased number of dead cells after co-culturing with all ZS-BGs.     

Foam Cells as Therapeutic Targets in Atherosclerosis with a Focus on the Regulatory Roles of Non-Coding RNAs

Atherosclerosis is a major cause of human cardiovascular disease, which is the leading cause of mortality around the world. Various physiological and pathological processes are involved, including chronic inflammation, dysregulation of lipid metabolism, development of an environment characterized by oxidative stress and improper immune responses. Accordingly, the expansion of novel targets for the treatment of atherosclerosis is necessary. In this study, we focus on the role of foam cells in the development of atherosclerosis. The specific therapeutic goals associated with each stage in the formation of foam cells and the development of atherosclerosis will be considered. Processing and metabolism of cholesterol in the macrophage is one of the main steps in foam cell formation. Cholesterol processing involves lipid uptake, cholesterol esterification and cholesterol efflux, which ultimately leads to cholesterol equilibrium in the macrophage. Recently, many preclinical studies have appeared concerning the role of non-encoding RNAs in the formation of atherosclerotic lesions. Non-encoding RNAs, especially microRNAs, are considered regulators of lipid metabolism by affecting the expression of genes involved in the uptake (e.g., CD36 and LOX1) esterification (ACAT1) and efflux (ABCA1, ABCG1) of cholesterol. They are also able to regulate inflammatory pathways, produce cytokines and mediate foam cell apoptosis. We have reviewed important preclinical evidence of their therapeutic targeting in atherosclerosis, with a special focus on foam cell formation.     

Evaluation of driver drowsiness using respiration analysis by thermal imaging on a driving simulator

In this paper, a new non-intrusive driver drowsiness detection method is introduced based on respiration analysis using facial thermal imaging. Drowsiness is the cause of many driving accidents all over the world. Drivers’ respiration system undergoes significant changes from wakefulness to drowsiness and can be used to detect drowsiness. Current respiration measurement methods are intrusive and uncomfortable making respiration the least measured vital sign during driving. In this paper, a new method is presented based on facial thermal imaging to analyze drivers’ respiration signal non-intrusively. Thirty subjects are tested in a car simulator. They are fully awake at the beginning and experience drowsiness during the tests. The mean and the standard deviation of the respiration rate and the inspiration-to-expiration time ratio are extracted from the subjects’ respiration signal. To detect drowsiness, the Support Vector Machine (SVM) and the K-Nearest Neighbor (KNN) classifiers are used. The Observer Rating of Drowsiness method is used for scoring the drowsiness level and validating the proposed method. The performance and the results of both methods are presented and compared. The results indicate that drowsiness can be detected with the accuracy of 90%, sensitivity of 92%, specificity of 85%, and precision of 91%.

     

Heteroscedastic linear feature extraction based on sufficiency conditions

Classification of high-dimensional data typically requires extraction of discriminant features. This paper proposes a linear feature extractor, called whitened linear sufficient statistic (WLSS), which is based on the sufficiency conditions for heteroscedastic Gaussian distributions. WLSS approximates, in the least squares sense, an operator providing a sufficient statistic. The proposed method retains covariance discriminance in heteroscedastic data, while it reduces to the commonly used linear discriminant analysis (LDA) in the homoscedastic case. Compared to similar heteroscedastic methods, WLSS imposes a low computational complexity, and is highly generalizable as confirmed by its consistent competence over various data sets.     

A method for designing power supply chain networks accounting for failure scenarios and preventive maintenance

A power grid is vulnerable and failures are inevitable. Failures decrease the power supply with an adverse effect on meeting the demand for electricity. Therefore, there is a need for a method to design power grid networks that result in the least possible disruption to the power supply when a failure occurs. In the literature, the focus has been on the design of the generation system without considering the transmission system or failures in the transmission system. Since power grids are integrated generation and transmission systems, each system will affect the other, so both generation and transmission systems need to be considered, as they are in this article. Methods developed for the structural modelling and analysis of supply chains are shown to be useful. The focus in this article is on describing a method using the supply chain construct for designing power grids that are relatively insensitive to failure in the integrated generation and transmission system. The efficacy of the method is illustrated using data from the Tehran Regional Electric Company. One of the findings is that targeted failures have a higher impact on decreasing the performance of the power grid than random failures. However, the focus is on the method rather than the results per se.     

Blasting pattern optimization using gene expression programming and grasshopper optimization algorithm to minimise blast-induced ground vibrations

Engineering with Computers - Blast-induced ground vibration is considered as one of the most hazardous phenomena of mine blasting, which can even cause casualties and severe damages to the adjacent...     

Smart aptamer-modified calcium carbonate nanoparticles for controlled release and targeted delivery of epirubicin and melittin into cancer cells in vitro and in vivo

To explore the effect of combination therapy of epirubicin (Epi) and melittin (Mel) to cancer cells, calcium carbonate nanoparticles (CCN), as carriers, were developed which were modified with MUC1-Dimer aptamers as targeting agents. Both Epi and Mel were delivered at the same time to cancer cells overexpressing the target of MUC1 aptamer, mucin 1 glycoproteins (MCF7 and C26 cells). CCN were prepared with a water-in-oil emulsion method. Epi and Mel were separately encapsulated in CCN and the nanoparticles were modified with MUC1-Dimer aptamers. In vitro studies, including MTT assay, flow cytometry analysis and fluorescence imaging were applied to investigate the targeting and cell proliferation inhibition capabilities of MUC1-Dimer aptamer-CCN-Mel complex and MUC1-Dimer aptamer-CCN-Epi complex in the target (MCF-7 and C26 cells) and nontarget (HepG2) cells. Also, the function of the developed complexes was analyzed using in vivo tumor growth inhibition. The release of Epi from MUC1-Dimer aptamer-CCN-Epi complex was pH-sensitive. Cellular uptake studies showed more internalization of the MUC1-Dimer aptamer-CCN-Epi complex into MCF-7 and C26 cells (target) compared to HepG2 cells (nontarget). Interestingly, the MUC1-Dimer aptamer-CCN-Mel complex and MUC1-Dimer aptamer-CCN-Epi complex indicated very low toxicity as compared to target cells. Moreover, co-delivery of Epi and Mel using the mixture of MUC1-Dimer aptamer-CCN-Mel complex and MUC1-Dimer aptamer-CCN-Epi complex exhibited strong synergistic cytotoxicity in MCF-7 and C26 cells. Furthermore, the presented complexes had a better function to control tumor growth in vivo compared to free Epi.