Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

The morphology and gas‐separation performance of membranes comprising multiwalled carbon nanotubes/polysulfone–Kapton

The development of desirable chemical structures and properties in nanocomposite membranes involve steps that need to be carefully designed and controlled. This study investigates the effect of adding multiwalled nanotubes (MWNT) on a Kapton–polysulfone composite membrane on the separation of various gas pairs. Data from Fourier transform infrared spectroscopy and scanning electron microscopy confirm that some studies on the Kapton–polysulfone blends are miscible on the molecular level. In fact, the results indicate that the chemical structure of the blend components, the Kapton–polysulfone blend compositions, and the carbon nanotubes play important roles in the transport properties of the resulting membranes. The results of gas permeability tests for the synthesized membranes specify that using a higher percentage of polysulfone (PSF) in blends resulted in membranes with higher ideal selectivity and permeability. Although the addition of nanotubes can increase the permeability of gases, it decreases gas pair selectivity. Furthermore, these outcomes suggest that Kapton–PSF membranes with higher PSF are special candidates for CO₂/CH₄ separation compared to CO₂/N₂ and O₂/N₂ separation. High CH₄, CO₂, N₂, and O₂ permeabilities of 0.35, 6.2, 0.34, and 1.15 bar, respectively, are obtained for the developed Kapton–PSF membranes (25/75%) with the highest percentage of carbon nanotubes (8%), whose values are the highest among all the resultant membranes. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43839.     

Air-breathing microbial fuel cell with enhanced performance using nanocomposite proton exchange membranes

This work aims to improve the performance of air-breathing microbial fuel cells (MFCs) through using hydrocarbon polymer based nanocomposite proton exchange membranes. Accordingly, nanocomposite membranes based on sulfonated poly(ether ether ketone) (SPEEK) and montmorillonite (MMT) were investigated for such an application. Although the incorporation of MMT into SPEEK membranes resulted in reduced oxygen permeability as well as proton conductivity, but the overall selectivity was found to be improved. MFC tests revealed that using the optimized nanocomposite membrane (SPEEK-70/MMT-3 wt%) results in a considerably higher open circuit voltage (OCV) compared to the corresponding neat membrane. Moreover, it was found that the SPEEK-70/MMT-3 wt% membrane is able to provide about 40% more power output than Nafion^®117. On the account of high proton conductivity, low oxygen permeability, high electrochemical performance, ease of preparation and low cost, hydrocarbon based nanocomposite PEMs could be considered as promising electrolytes to enhance the performance of MFCs.     

Novel Homozygous Missense Variant in GJA3 Connexin Domain Causing Congenital Nuclear and Cortical Cataracts

Congenital cataracts (CC) are responsible for approximately one-tenth of childhood blindness cases globally. Here, we report an African American family with a recessively inherited form of CC. The proband demonstrated decreased visual acuity and bilateral cataracts, with nuclear and cortical cataracts in the right and left eye, respectively. Exome sequencing revealed a novel homozygous variant (c.563A > G; p.(Asn188Ser)) in GJA3, which was predicted to be pathogenic by structural analysis. Dominantly inherited variants in GJA3 are known to cause numerous types of cataracts in various populations. Our study represents the second case of recessive GJA3 allele, and the first report in African Americans. These results validate GJA3 as a bona fide gene for recessively inherited CC in humans.     

Robust weighted graph transformation matching for rigid and nonrigid image registration

This paper presents an automatic point matching algorithm for establishing accurate match correspondences in two or more images. The proposed algorithm utilizes a group of feature points to explore their geometrical relationship in a graph arrangement. The algorithm starts with a set of matches (including outliers) between the two images. A set of nondirectional graphs is then generated for each feature and its K nearest matches (chosen from the initial set). Using the angular distances between edges that connect a feature point to its K nearest neighbors in the graph, the algorithm finds a graph in the second image that is similar to the first graph. In the case of a graph including outliers, the algorithm removes such outliers (one by one, according to their strength) from the graph and re-evaluates the angles until the two graphs are matched or discarded. This is a simple intuitive and robust algorithm that is inspired by a previous work. Experimental results demonstrate the superior performance of this algorithm under various conditions, such as rigid and nonrigid transformations, ambiguity due to partial occlusions or match correspondence multiplicity, scale, and larger view variation.     

Oxidation Behavior of Nanostructured Ni-5Al Coating. A case Study on Monophase Coatings

Protection of Metals and Physical Chemistry of Surfaces - Oxidation behavior of nanostructured Ni-5Al HVOF coatings was studied. For this purpose, isothermal oxidation of the free standing coatings...     

Vision-based 3-D trajectory tracking for unknown environments

This paper describes a vision-based system for 3-D localization of a mobile robot in a natural environment. The system includes a mountable head with three on-board charge-coupled device cameras that can be installed on the robot. The main emphasis of this paper is on the ability to estimate the motion of the robot independently from any prior scene knowledge, landmark, or extra sensory devices. Distinctive scene features are identified using a novel algorithm, and their 3-D locations are estimated with high accuracy by a stereo algorithm. Using new two-stage feature tracking and iterative motion estimation in a symbiotic manner, precise motion vectors are obtained. The 3-D positions of scene features and the robot are refined by a Kalman filtering approach with a complete error-propagation modeling scheme. Experimental results show that good tracking and localization can be achieved using the proposed vision system.     

Performance of Belief Propagation for Decoding LDPC Codes in the Presence of Channel Estimation Error

In this paper, we investigate the performance of the belief propagation (BP) algorithm for decoding low-density parity-check codes over the additive white Gaussian noise channel when there is an incorrect estimate of the channel signal-to-noise ratio (SNR) (referred to as "SNR mismatch") at the decoder. At the extremes for over- and underestimation of SNR, the performance of BP tends to that of min-sum algorithm and the channel bit-error rate, respectively. Our results for regular codes indicate that the sensitivity to mismatch increases by increasing the variable-node degree and by decreasing the check-node degree. The effect of variable-node degree, however, appears to be more profound, such that at a given rate, the codes with the smallest variable and check degrees are more robust against SNR mismatch. For irregular codes, by comparing the thresholds of a few ensembles, we demonstrate that the ensemble which performs better in the absence of mismatch can perform worse in the presence of it. To obtain our asymptotic results, we propose a computationally efficient method based on the Gaussian approximation of density evolution in the presence of SNR mismatch. We also show that the asymptotic results are consistent with simulation results for codes with finite block lengths     

Control and Navigation Framework for Quadrotor Helicopters

This paper presents the development of a nonlinear quadrotor simulation framework together with a nonlinear controller. The quadrotor stabilization and navigation problems are tackled using a nested loops control architecture. A nonlinear Backstepping controller is implemented for the inner stabilization loop. It asymptotically tracks reference attitude, altitude and heading trajectories. The outer loop controller generates the reference trajectories for the inner loop controller to reach the desired waypoint. To ensure boundedness of the reference trajectories, a PD controller with a saturation function is used for the outer loop. Due to the complexity involved in controller development and testing, a simulation framework has been developed. It is based on the Gazebo 3D robotics simulator and the Open Dynamics Engine (ODE) library. The framework can effectively facilitate the development and validation of controllers. It has been released and is available at Gazebo quadrotor simulator (2012).