Analyzing the determinants of carbon emissions from transportation in European countries: the role of renewable energy and urbanization

Clean Technologies and Environmental Policy - The continuous growth of transport sector and the increase in carbon emissions from transportation attract the attention of policy makers in...     

Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Journal of Signal Processing Systems - Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful...     

Experimental and numerical studies on the determination of twist drill temperature in dry drilling: A new approach

In this paper, the influences of the spindle speed and feed rate on the drill temperature responses have been investigated. A new experimental approach was developed to measure drill temperature in drilling process. Drill temperatures were measured by inserting standard thermocouples through the coolant (oil) hole of TiAlN-coated carbide drills. Experimental parameters used in the study has based on Taguchi’s method. Experimental study was conducted by using two different workpiece materials, AISI 1040 steel and Al 7075-T651. The drill bit temperature was predicted using a numerical calculation with Third Wave AdvantEdge^TM Lagrangian based on explicit finite element analysis software. The results obtained from experimental study and finite element analyses (FEA) were compared. Good agreement between the measured and analyzed temperature results was found in dry drilling process.     

A microfluidic toolbox for cell fusion

Cellular fusion is a key process in many fields ranging from historical gene mapping studies and monoclonal antibody production, through to cell reprogramming. Traditional methodologies for cell fusion rely on the random pairing of different cell types and generally result in low and variable fusion efficiencies. These approaches become particularly limiting where substantial numbers of bespoke one‐to‐one fusions are required, for example, for in‐depth studies of nuclear reprogramming mechanisms. In recent years, microfluidic technologies have proven valuable in creating platforms where the manipulation of single cells is highly efficient, rapid and controllable. These technologies also allow the integration of different experimental steps and characterisation processes into a single platform. Although the application of microfluidic methodologies to cell fusion studies is promising, current technologies that rely on static trapping are limited both in terms of the overall number of fused cells produced and their experimental accessibility. Here we review some of the most exciting breakthroughs in core microfluidic technologies that will allow the creation of integrated platforms for controlled cell fusion at high throughput. © 2015 Society of Chemical Industry     

New classification techniques for electroencephalogram (EEG) signals and a real-time EEG control of a robot

This paper studies the state-of-the-art classification techniques for electroencephalogram (EEG) signals. Fuzzy Functions Support Vector Classifier, Improved Fuzzy Functions Support Vector Classifier and a novel technique that has been designed by utilizing Particle Swarm Optimization and Radial Basis Function Networks (PSO-RBFN) have been studied. The classification performances of the techniques are compared on standard EEG datasets that are publicly available and used by brain–computer interface (BCI) researchers. In addition to the standard EEG datasets, the proposed classifier is also tested on non-EEG datasets for thorough comparison. Within the scope of this study, several data clustering algorithms such as Fuzzy C-means, K-means and PSO clustering algorithms are studied and their clustering performances on the same datasets are compared. The results show that PSO-RBFN might reach the classification performance of state-of-the art classifiers and might be a better alternative technique in the classification of EEG signals for real-time application. This has been demonstrated by implementing the proposed classifier in a real-time BCI application for a mobile robot control.     

GC–MS analysis of oxysterols and their formation in cultivated liver cells (HepG2)

Oxysterols play a key role in many (patho)physiological processes and they are potential biomarkers for oxidative stress in several diseases. Here we developed a rapid gas chromatographic-mass spectrometry-based method for the separation and quantification of 11 biologically relevant oxysterols bearing hydroxy, epoxy, and dihydroxy groups. Efficient chromatographic separation (resolution ≥ 1.9) was achieved using a medium polarity 35%-diphenyl/65%-dimethyl polysiloxane stationary phase material (30 m × 0.25 mm inner diameter and 0.25 μm film thickness). Based on thorough analysis of the fragmentation during electron ionization we developed a strategy to deduce structural information of the oxysterols. Optimized sample preparation includes (i) extraction with a mixture of n-hexane/iso-propanol, (ii) removal of cholesterol by solid phase extraction with unmodified silica, and (iii) trimethylsilylation. The method was successfully applied on the analysis of brain samples, showing consistent results with previous studies and a good intra- and interday precision of ≤20%. Finally, we used the method for the investigation of oxysterol formation during oxidative stress in HepG2 cells. Incubation with tert-butyl hydroperoxide led to a massive increase in free radical formed oxysterols (7-keto-chol > 7β-OH-chol >> 7α-OH-chol), while 24 h incubation with the glutathione peroxidase 4 inhibitor RSL3 showed no increase in oxidative stress based on the oxysterol pattern. Overall, the new method described here enables the robust analysis of a biologically meaningful pattern of oxysterols with high sensitivity and precision allowing us to gain new insights in the biological formation and role of oxysterols.     

Wet Forward Combustion for Heavy Oil Recovery

The purpose of this study was to perform wet forward combustion experiments for Bati Kozluca heavy oil under different experimental conditions. In the experiments, a vertical combustion tube was packed with crushed limestone and saturated with crude oil and water. A total of five wet combustion tube runs were conducted. It was observed that peak temperatures were higher when stabilized combustion was achieved and decreased as the combustion front approached the outlet of combustion tube. In wet combustion experiments, excess carbon dioxide productions were observed due to the decomposition of carbonate minerals. The concentration of carbon dioxide increased after the injection of water while the concentration of the oxygen and carbon monoxide decreased. Atomic H/C ratio of the fuel consumed decreased as the average peak temperature increased. Fuel consumption rate also decreased as the water-air ratio increased. The oil recovery was increased with the water injection until the optimum value. After this point, a decrease in oil recovery was observed due to the decrease in peak temperatures in Bati Kozluca crude oil. The main advantage of wet combustion was to reduce air requirements and improve the sweep efficiency by expanding the steam plateau region. Since most of the oil was displaced ahead of the burning front, the steam plateau becomes the primary driving mechanism for oil production.     

Elastic stability and buckling loads of multi-span nonuniform beams,shafts and frames on rigid or elastic supports by finite element method using planar uniform line elements

A numerical computer method using planar flexural finite line element for the determination of buckling loads of beams, shafts and frames supported by rigid or elastic bearings is presented. Buckling loads and the corresponding mode vectors are determined by the solution of a linear set of eigenvalue equations of elastic stability. The elastic stability matrix is determined as the product of the bifurcation sidesway flexibility matrix and the second order bifurcation sidesway stiffness matrix which is formed using the element bifurcation sidesway stiffness matrices. The bifurcation sidesway flexibility matrix is determined by partitioning the inverse of the global external stiffness matrix of the system which is formed from the element data using the element stiffness matrices. The method is directly applicable to the determination of the buckling loads of beams and frames partially or fully supported by elastic foundations where the foundation stiffness is approximated by a discrete set of springs. The method of the article provides means to consider complex boundary conditions in buckling problems with ease. Four numerical examples are included to illustrate the industrial applications of the contents of the article.