Exhaust emission profiling of fatty acid methyl esters and NOx control studies using selective synthetic and natural additives

Clean Technologies and Environmental Policy - The present study was focused on the optimized biodiesel production using Moringa oleifera (M. oleifera) and rice bran oils, characterization, and...     

Popularity prediction of movies: from statistical modeling to machine learning techniques

Multimedia Tools and Applications - Film industries all over the world are producing several hundred movies rapidly and grabbing the attraction of people of all ages. Every movie producer is of...     

Experimental investigation of multiphase flow behavior in drilling annuli using high speed visualization technique

Imaging with high definition video camera is an important technique to visualize the drilling conditions and to study the physics of complex multiphase flow associated with the hole cleaning process. The main advantage of visualizing multiphase flow in a drilling annulus is that the viewer can easily distinguish fluid phases, flow patterns and thicknesses of cutting beds. In this paper the hole cleaning process which involves the transportation of cuttings through a horizontal annulus was studied. The two-phase (solid-liquid) and the three-phase (solid-liquid-gas) flow conditions involved in this kind of annular transportation were experimentally simulated and images were taken using a high definition camera. Analyzing the captured images, a number of important parameters like velocities of different phases, heights of solid beds and sizes of gas bubbles were determined. Two different techniques based on an image analysis software and MATLAB coding were used for the determinations. The results were compared to validate the image analyzing methodology. The visualization technique developed in this paper has a direct application in investigating the critical conditions required for efficient hole cleaning as well as in optimizing the mud program during both planning and operational phases of drilling. Particularly, it would be useful in predicting the cuttings transport performance, estimating solid bed height, gas bubble size, and mean velocities of bubbles/particles.     

A new nonparametric double exponentially weighted moving average control chart

There are many practical situations where the underlying distribution of the quality characteristic either deviates from normality or it is unknown. In such cases, practitioners often make use of the nonparametric control charts. In this paper, a new nonparametric double exponentially weighted moving average control chart on the basis of the signed-rank statistic is proposed for monitoring the process location. Monte Carlo simulations are carried out to obtain the run length characteristics of the proposed chart. The performance comparison of the proposed chart with the existing parametric and nonparametric control charts is made by using various performance metrics of the run length distribution. The comparison showed the superiority of the suggested chart over its existing parametric and nonparametric counterparts. An illustrative example for the practical implementation of the proposed chart is also provided by using the industrial data set.     

Development of high performance amine functionalized zeolitic imidazolate framework (ZIF-8)/cellulose triacetate mixed matrix membranes for CO2/CH4 separation

High cost and complex fabrication process of inorganic membranes and lower position of pristine polymeric membranes in the Robeson upper bound curve urged the researchers to develop mixed matrix membranes (MMMs). Cellulose acetate being most commercially used polymer, dominates the market of CO₂ separation mainly because of low cost and environmental friendly resource. In the present study, MMMs consists of amine functionalized zeolitic imidazolate framework (NH₂-ZIF-8) and cellulose triacetate were fabricated for the first time. NH₂-ZIF-8 was used as a filler because the pore size of ZIF-8 is between the kinetic diameter of separating gases (CO₂ and CH₄). Moreover,  NH₂ group attached on the surface of ZIF-8 has affinity with condensable gases like CO₂. Morphology, crystallinity, tensile strength and functional groups of fabricated membranes were investigated using different analytical techniques. Results revealed that the increase of feed pressure has increased CO₂ permeability and decreased permselectivity. However, improvements in gas separation performance were observed with the addition of nanofiller. Best position in Robeson's upper bound curve at 4 bar was obtained with 10 wt% loading with CO₂ permeability and CO₂/CH₄ permselectivity of 218 barrer and 13.84, respectively. The improvement in the gas separation performance with loading is attributed to the increased diffusion coefficients as well as solubility coefficients, which was increased to 33% and 3.8%, respectively.     

Designing Stimuli-Responsive Upconversion Nanoparticles that Exploit the Tumor Microenvironment

Tailoring personalized cancer nanomedicines demands detailed understanding of the tumor microenvironment. In recent years, smart upconversion nanoparticles with the ability to exploit the unique characteristics of the tumor microenvironment for precise targeting have been designed. To activate upconversion nanoparticles, various bio-physicochemical characteristics of the tumor microenvironment, namely, acidic pH, redox reactants, and hypoxia, are exploited. Stimuli-responsive upconversion nanoparticles also utilize the excessive presence of adenosine triphosphate (ATP), riboflavin, and Zn²⁺ in tumors. An overview of the design of stimulus-responsive upconversion nanoparticles that precisely target and respond to tumors via targeting the tumor microenvironment and intracellular signals is provided. Detailed understanding of the tumor microenvironment and the personalized design of upconversion nanoparticles will result in more effective clinical translation.     

Reliability-based fault analysis models with industrial applications: A systematic literature review

Effective and early fault detection and diagnosis techniques have tremendously enhanced over the years to ensure continuous operations of contemporary complex systems, control cost, and enhance safety in assets-intensive industries, including oil and gas, process, and power generation. The objective of this work is to understand the development of different fault detection and diagnosis methods, their applications, and benefits to the industry. This paper presents a contemporary state-of-the-art systematic literature survey focusing on a comprehensive review of the models for fault detection and their industrial applications. This study uses advanced tools from bibliometric analysis to systematically analyze over 500 peer-reviewed articles on focus areas published since 2010. We first present an exploratory analysis and identify the influential contributions to the field, authors, and countries, among other key indicators.  A network analysis is presented to unveil and visualize the clusters of the distinguishable areas using a co-citation network analysis. Later, a detailed content analysis of the top-100 most-cited papers is carried out to understand the progression of fault detection and artificial intelligence–based algorithms in different industrial applications. The findings of this paper allow us to comprehend the development of reliability-based fault analysis techniques over time, and the use of smart algorithms and their success. This work helps to make a unique contribution toward revealing the future avenues and setting up a prospective research road map for asset-intensive industry, researchers, and policymakers.     

Ferroelectric,dielectric, magnetic,structural and photocatalytic properties of Co and Fe doped LaCrO3 perovskite synthesized via micro-emulsion route

In the present investigation, La_1-xCo_xCr_1-yFe_yO₃ (x,y = 0.0, 0.12, 0.36, 0.60) perovskite was fabricated via a facile micro-emulsion route. The synthesized perovskites were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) techniques to examine the effect of Co and Fe ions on the physico-chemical properties. The ferroelectric, dielectric, and magnetic properties of La_1-xCo_xCr_1-yFe_yO₃ were changed significantly as a function of dopants contents (Co and Fe ions). Outcomes revealed that the dielectric, ferroelectric and magnetic properties of LaCrO₃ perovskite can be tuned significantly via Co and Fe doping and La_0.40Co_0.60Cr_0.40Fe_0.60O₃ have potential for photocatalytic dye removal under (visible) light expoure. The photocatalytic activity (PCA) of the pristine LaCrO₃ and La_0.40Co_0.60Cr_0.40Fe_0.60O₃ photocatalyst was evaluated under (visible) light irradiation for crystal violet (CV) dye. Experimental results revealed that La_0.40Co_0.60Cr_0.40Fe_0.60O₃ photocatalyst degrdae almost 77.21% CV dye with the rate constant value of 0.01475 min^?1. In the presence of isopropyl alcohol (IPA) scavenger, the PCA of the La_0.40Co_0.60Cr_0.40Fe_0.60O₃ photocatalyst and rate constant value of the photocatalytic reaction decreased to 32.5% and 0.00491 min^?1, suggesting the superoxide as main active specie. Results revealed that Co and Fe doping doped material is efficient for photocatalytic presentations under solar light expoure.     

NS-2 based simulation framework for cognitive radio sensor networks

In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs) which is an attempt to combine the useful properties of wireless sensor networks and cognitive radio networks. The existing simulation models for cognitive radios cannot be extended for this purpose as they do not consider the strict energy constraint in wireless sensor networks. Our proposed model considers the limited energy available for wireless sensor nodes that constrain the spectrum sensing process—an unavoidable operation in cognitive radios. Our model has been thoroughly tested by performing experiments in different scenarios of CRSNs. The results generated by the model have been found accurate which can be considered for realization of CRSNs.