Digital Microfluidics for Manipulation and Analysis of a Single Cell

The basic structural and functional unit of a living organism is a single cell. To understand the variability and to improve the biomedical requirement of a single cell, its analysis has become a key technique in biological and biomedical research. With a physical boundary of microchannels and microstructures, single cells are efficiently captured and analyzed, whereas electric forces sort and position single cells. Various microfluidic techniques have been exploited to manipulate single cells through hydrodynamic and electric forces. Digital microfluidics (DMF), the manipulation of individual droplets holding minute reagents and cells of interest by electric forces, has received more attention recently. Because of ease of fabrication, compactness and prospective automation, DMF has become a powerful approach for biological application. We review recent developments of various microfluidic chips for analysis of a single cell and for efficient genetic screening. In addition, perspectives to develop analysis of single cells based on DMF and emerging functionality with high throughput are discussed.     

Structure–phase state of the surface layers in rails subjected to differential hardening

A layer-by-layer analysis of the structures, the phase compositions, and the defect substructures of differentially hardened rails has been carried by optical and transmission electron microscopy. It is found that the material volume of the rail head fillet is cooled faster than the volume located along the central axis.     

Quality enhancement of the abundant under‐valued crustacean,lobster krill (Munida spp.), during its chilled storage

Lobster krill (Munida genus) represents an under‐valued crustacean frequently caught on European fishing banks. In this work, its sensory, microbiological and biochemical qualities were evaluated during chilled storage. Additionally, the effects of a prestorage antimelanosic treatment consisting of soaking in sodium metabisulphite (SMB) solutions at two different concentrations (0.25% and 0.75%) were also studied. SMB prestorage treatment provided lobster specimens that still exhibited acceptable sensory quality after 10 days of storage, while control specimens were unacceptable at that time. SMB treatment also resulted in a significant (P < 0.05) inhibition of microbial growth, mainly of Enterobacteriaceae, psychrotrophes and proteolytic bacteria. Low lipid oxidation levels were observed for all batches; however, a significantly higher (P < 0.05) retention of polyunsaturated fatty acids was found in SMB‐treated lobster, especially in the 0.75% SMB batch. The results presented here open the way to the potential commercialisation of currently under‐utilised lobster krill as a chilled product.     

Cathode plasma electrolytic deposition of Al2O3 coatings doped with SiC particles

Semiconductor particles doped Al₂O₃ coatings were prepared by cathode plasma electrolytic deposition in Al(NO₃)₃ electrolyte dispersed with SiC micro- and nano-particles (average particle sizes of 0.5–1.7?µm and 40?nm respectively). The effects of the concentrations and particle sizes of the SiC on the microstructures and tribological performances of the composite coatings were studied. In comparison with the case of dispersing with SiC microparticles, the dispersion of SiC nanoparticles in the coatings was more uniform. When the concentration of SiC nanoparticles was 5?g/L, the surface roughness of the composite coating was reduced by 63%, compared with that of the unmodified coating. Friction results demonstrated that the addition of 5?g/L SiC nanoparticles reduced the friction coefficient from 0.60 to 0.38 and decreased the wear volume under dry friction. The current density and bath voltage were measured to analyze the effects of SiC particles on the deposition process. The results showed that the SiC particles could alter the electrical behavior of the coatings during the deposition process, weaken the bombardment of the plasma, and improve the structures of the coatings.     

Relationship Between the Thermodynamic Parameters,Structure, and Anticorrosion Properties of Al-Zr-Ni-Fe-Y Alloys

Metallurgical and Materials Transactions A - The influence of the chemical composition on the crystallization process, amorphous phase formation, and the anticorrosion properties of Al-Zr-Ni-Fe-Y...     

Optimal Placement of Dampers on Multistorey Frames Using Dynamic Analysis

Strength of Materials - The use of a damping system is one of the seismic protection systems that improve the seismic response of structures. The proposed methodology estimates the location (which...     

Effect of the Porous Skeletal Iron Structure on the Infiltration of Aluminum Melts

Powder Metallurgy and Metal Ceramics - The infiltration of aluminum melts into porous metal skeletons produced by powder metallurgy methods, including 3D printing, under a pressure gradient was...     

A Method of Transferring the Unit of Power of High-Intensity Laser Radiation

Measurement Techniques - A method is proposed for transferring the unit of mean power of laser radiation by means of measuring high-intensity power (kilowatts), with the possibility of constant...     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.