Semi-automatic measurement of rigid gas-permeable contact lens movement in keratoconus patients using blinking images

Purpose

To introduce a method for estimation of the rigid gas-permeable contact lens (RGP) movement.

Study of Pressure Effects on the Elastic Stability and Optical Treatment of Co<Subscript>2</Subscript>VAl using GGA+U

First-principles calculations of the elastic and optical properties of Co₂VAl compound under pressure are performed in the framework of density functional theory. Applying pressure causes elastic stability, hardness, Young’s modulus and Shear modulus and Debye temperature. Also, Co₂VAl shows higher ductility and anisotropy under stress. Using GGA + U method, it is found that Co₂VAl has 100 % spin polarization at the Fermi level and its spin flip gap is increased by applying pressure. The Co₂VAl response to incident light is positive only in the visible area for all pressures, and its peak is shifted to higher energies under pressure. Also, in the visible range, a peak is observed for absorption and conduction which is increased by applying pressure.     

A novel approach to develop the control of Telbot using ANFIS for nuclear hotcells

This paper develops an improved controller for Telbot. Telbot is a new 6 DOF tele-robot, with special kinematic design, famous for working in nuclear hotcells. The recent controllers are based on simple and improved PID controllers, with visible tracking error. In this project, an ANFIS controller was designed and trained for controlling this tele-robot. The proposed controller generates an appropriate torque for reaching desired state, without any error. The controller was initialized with if-then rules. The training includes online and offline processes. The offline processes have light loads, and prepaid more than 90% of system desired, but the online processes do the last critical 10%, and remove all the errors. The controller is describing the high degree of nonlinear dynamics behavior of the Telbot. The final simulation shows the error-less tracking.     

Fire‐retarding properties of nanowollastonite in particleboard

Effects of wollastonite nanofibers on fire‐retarding properties of particleboard were studied here. Nanowollastonite (NW) was applied at 5%, 10%, 15%, and 20% based on the dry weight of wood particles. The size range of wollastonite nanofibers was 30 to 110 nm. Two application methods of NW were used: surface application (SA) in which NW was mixed with a water‐based paint and sprayed on the specimens, and internal application (IA) in which NW was mixed with the urea‐formaldehyde resin. Density was kept constant at 0.68 g/cm³ for all treatments. Specimens of 150 × 130 × 9 mm were prepared, and fire‐retarding properties were measured using 2 apparatuses: slide fire test apparatus and fixed fire test apparatus. The obtained results indicated that most fire‐retarding properties were improved with the increase in NW content up to 15% when applied internally. More than this amount resulted in decreasing of properties that was partly due to the less wood‐chips content and partly due to the absorption of resin by the NW fibers. Surface application showed higher improving effects on the properties. It can be concluded that SA of NW is more effective in improving fire‐retarding properties of particleboard; furthermore, 10% of NW is recommended as an optimum level of consumption.     

Stability and extraction study of phenolic wastewater treatment by supported liquid membrane using tributyl phosphate and sesame oil as liquid membrane

Phenols pose a risk to the environment and to human health. Phenol and its derivatives are toxic pollutants, frequently found in surface and tap waters, and in aqueous effluents from various manufacturing processes. In this paper, an experimental study regarding transport of phenol through a supported liquid membrane (SLM) using tributyl phosphate (TBP) and sesame oil as liquid membrane (LM) was performed. Factors affecting permeation of phenol such as initial phenol concentration, carrier concentration, feed phase pH and stripping phase concentration were analyzed using Taguchi method. Optimal experimental condition of phenol transport was obtained using analysis of variance (ANOVA) after 7 h extraction (feed concentration: 200 mg/L; carrier concentration (%TBP): 40%; feed pH: 2; strip phase concentration: 1.1 M). Mass transfer coefficient for this system was evaluated, and compared with similar works, and it was shown that it has the highest mass transfer rate. In addition to transport study, stability of the membrane was investigated by examination of stripping phase concentration, carrier concentration and salt concentration effects.     

Aqueous free-radical polymerization of PEGMEMA macromer: kinetic studies via an on-line 1H NMR technique

Free-radical polymerization of polyethylene glycol methyl ether methacrylate macromer (PEGMEMA) was studied in aqueous media and in the presence of potassium persulfate (KPS) as water soluble initiator. An on-line nuclear magnetic resonance (NMR) method was applied to record the reaction data and determine the monomer conversion at various times during the polymerization reaction progress. ¹H NMR spectrum of reaction mixture containing monomer, initiator and resultant polymer was continuously recorded in NMR instrument with the increase of reaction time. By processing the obtained data from NMR spectrum, the rate equation can be derived and reaction order can be determined with regard to monomer and initiator concentration. In other words, to determine the order of polymerization with regard to the concentration of reactants in free-radical polymerization of PEGMEMA, macromer samples with different amounts of monomer and KPS were prepared and polymerized at 50?°C. Orders of reaction with respect to monomer and initiator molar concentrations were equal to 1.025 and 0.480, respectively. The obtained values for reaction orders in this study were consistent with the classical kinetic rate equation in which the dependency of polymerization rate (R _p) on monomer and initiator concentrations was equal to 1 and 0.5, respectively. To measure polymerization activation energy (E _a), the effect of reaction temperature on the polymerization rate was investigated and E _a?=?37.08?kJ/mol was obtained at the temperature range of 40?C50?°C.     

Modulating the Mechanical Performance of Macroscale Fibers through Shear‐Induced Alignment and Assembly of Protein Nanofibrils

Protein‐based fibers are used by nature as high‐performance materials in a wide range of applications, including providing structural support, creating thermal insulation, and generating underwater adhesives. Such fibers are commonly generated through a hierarchical self‐assembly process, where the molecular building blocks are geometrically confined and aligned along the fiber axis to provide a high level of structural robustness. Here, this approach is mimicked by using a microfluidic spinning method to enable precise control over multiscale order during the assembly process of nanoscale protein nanofibrils into micro‐ and macroscale fibers. By varying the flow rates on chip, the degree of nanofibril alignment can be tuned, leading to an orientation index comparable to that of native silk. It is found that the Young's modulus of the resulting fibers increases with an increasing level of nanoscale alignment of the building blocks, suggesting that the mechanical properties of macroscopic fibers can be controlled through varying the level of ordering of the nanoscale building blocks. Capitalizing on strategies evolved by nature, the fabrication method allows for the controlled formation of macroscopic fibers and offers the potential to be applied for the generation of further novel bioinspired materials.     

Conceptual design optimization of rectilinear building frames: A knapsack problem approach

This article presents an automated technique for preliminary layout (conceptual design) optimization of rectilinear, orthogonal building frames in which the shape of the building plan, the number of bays and the size of unsupported spans are variables. It adopts the knapsack problem as the applied combinatorial optimization problem, and describes how the conceptual design optimization problem can be generally modelled as the unbounded multi-constraint multiple knapsack problem. It discusses some special cases, which can be modelled more efficiently as the single knapsack problem, the multiple-choice knapsack problem or the multiple knapsack problem. A knapsack contains sub-rectangles that define the floor plan and the location of columns. Particular conditions or preferences for the conceptual design can be incorporated as constraints on the knapsacks and/or sub-rectangles. A bi-objective knapsack problem is defined with the aim of obtaining a conceptual design having minimum cost and maximum plan regularity (minimum structural eccentricity). A multi-objective ant colony algorithm is formulated to solve the combinatorial optimization problem. A numerical example is included to demonstrate the application of the present method and the robustness of the algorithm.     

A passive mechanism for thermal stress regulation in micro-machined beam-type structures

In this article, a passive mechanism for thermal stress regulation in micro-bridge structures is proposed. The mechanism is essentially a set of precisely designed parallel chevron beams that replace one of the fixed ends of the micro-bridge. The axial stress/force of the beam is determined by utilizing a sensing mechanism that makes use of two side-electrodes and the electromechanical buckling of the micro-bridge toward one of them. A combination of analytical and finite element methods has been employed for the modeling of the proposed mechanism. It has been demonstrated that the regulator mechanism has negligible dynamic effect on the sensing micro-beam. The model takes into account the effect of electric field fringes between the electrically charged bodies. It has been shown that there is a time delay between the moment that the pull-in occurs and the instant that the sensing beam rests on a side-electrode. The results of the modeling are verified by experiment on two devices fabricated using MetalMUMPs^? fabrication technology. The thermal stress sensitivities of the devices are positive and their residual stresses are in excellent agreement.     

An improved model-based evolutionary algorithm for multi-objective optimization

The basic idea in the estimation of distribution algorithms is the replacement of heuristic operators with machine learning models such as regression models, clustering models, or classification models. So, recently, the model-based evolutionary algorithms (MBEAs) have been suggested in three groups: The estimation of distribution algorithms (EDAs), surrogate assisted evolutionary algorithms, and the inversed models to map from the objective space to the decision space. In this article, a new approach, based on an inversed model of Gaussian process and random forest framework, is proposed. The main idea is applying the process of random forest variable importance with a random grouping that determines some of the best assignment of decision variables to objective functions in order to form a Gaussian process in inverse models that maps to decision space the rich solutions which are discovered from objective space. Then these inverse models through sampling the objective space generate offspring. The proposed algorithm has been tested on the benchmark test suite for evolutionary algorithms (modified Deb K, Thiele L, Laumanns M, Zitzler E (DTLZ), and Walking Fish Group (WFG)) and indicates that the proposed method is a competitive and promising approach.