A novel ACO–GA hybrid algorithm for feature selection in protein function prediction

Protein function prediction is an important problem in functional genomics. Typically, protein sequences are represented by feature vectors. A major problem of protein datasets that increase the complexity of classification models is their large number of features. Feature selection (FS) techniques are used to deal with this high dimensional space of features. In this paper, we propose a novel feature selection algorithm that combines genetic algorithms (GA) and ant colony optimization (ACO) for faster and better search capability. The hybrid algorithm makes use of advantages of both ACO and GA methods. Proposed algorithm is easily implemented and because of use of a simple classifier in that, its computational complexity is very low. The performance of proposed algorithm is compared to the performance of two prominent population-based algorithms, ACO and genetic algorithms. Experimentation is carried out using two challenging biological datasets, involving the hierarchical functional classification of GPCRs and enzymes. The criteria used for comparison are maximizing predictive accuracy, and finding the smallest subset of features. The results of experiments indicate the superiority of proposed algorithm.     

Development of a 2-D 2-group neutron noise simulator for hexagonal geometries

In this paper, the development of a neutron noise simulator for hexagonal-structured reactor cores using both the forward and the adjoint methods is reported. The spatial discretisation of both 2-D 2-group static and dynamic equations is based on a developed box-scheme finite difference method for hexagonal mesh boxes. Using the power iteration method for the static calculations, the 2-group neutron flux and its adjoint with the corresponding eigenvalues are obtained by the developed static simulator. The results are then benchmarked against the well-known CITATION computer code. The dynamic calculations are performed in the frequency domain which leads to discarding of the time discretisation. Then, the developed 2-D 2-group neutron noise simulator calculates both the discretised forward and the adjoint reactor transfer function between a point source and its induced neutron noise, by assuming the neutron noise source as an “absorber of variable strength” type. The neutron noise induced by a “vibrating absorber” type of noise source may also be modeled using the calculated transfer function. The viability of the simulator is verified for different benchmark cases.     

Clarifying the effects of comonomer distribution between short and long chains on physical and mechanical properties of ethylenic copolymers

In this paper, two Zigler-Natta catalysts (ZNCs) were used to synthesize a commercially available linear low-density polyethylene (LLDPE), widely used in the packaging industry, on an industrial scale. The catalysts differ only in their ability to distribute comonomers between short and long chains. Both catalysts were fully characterized in the first section, and two similar ethylene/1-butene copolymers were made using them. Afterward, the produced copolymers were fully characterized using different techniques; namely, differential scanning calorimetry (DSC), successive self-nucleation and annealing (SSA), oxygen induction time (OIT), melt flow index (MFI), rheometric mechanical spectroscopy (RMS), and a wide range of mechanical experiments. It was revealed that while the presence of comonomers in short chains can reduce their resistance against oxidation (by more than 30%) and can cause a dramatic change in friction coefficients (by more than 20%), some of the other main mechanical properties of the made copolymers were independent of comonomer distribution between long and short chains. In addition, it was shown that ethylenic copolymers' strain hardening modulus (SHM) takes advantage of the homogenous distribution.     

The Effects of SiO2/Al2O3 and H2O/Al2O3 Molar Ratios on SAPO-34 Catalyst in the Methanol to Olefin Process

Silicon - Informed through synthesis and characterization of NH 3 TPD, BET techniques, the current study investigated the right contribution of silicon and water content on a 9 sample SAPO-34...     

Simple Method for Prediction of the Standard Gibbs Free Energy of Formation of Energetic Compounds

A reliable simple method for prediction of the standard Gibbs energy of formation (Δ_fG^θ) of energetic compounds containing nitroaromatic, acyclic, and cyclic nitramine, nitrate ester, and nitroaliphatic compounds is introduced herein. The method is based on the contribution of elemental composition (Δ_fG_elem^θ) and the correcting function for the presence of additive and non‐additive molecular fragments (Δ_fG_corr^θ). In presence of some molecular moieties, Δ_fG_corr^θ may increase or decrease the value of Δ_fG_elem^θ, depending on the intermolecular interactions. The experimental root‐mean‐square error (RMSE) of the novel correlation (22.7 kJ mol⁻¹) is quite good. For some energetic compounds, where the computed values of two complex models of the quantitative structure‐property relationship (QSPR) theory were available, the experimental RMSE developed by the new method is smaller than the values obtained by QSPR method.     

A Flat Polymeric Membrane Sensor for Carbon Dioxide/Nitrogen Gas Mixture

A gas sensor was developed to measure the concentration of binary gas mixtures. This sensor works based on the permeability change of different gas mixtures across the polymeric membranes. Although high values of permeability and selectivity are needed for an ideal separation, the performance of this sensor mainly depends on the permeability factor. Polysulfone and silicone rubber were applied as the membrane base and coat, respectively. Moreover, in contrast to existing polymeric sensors that use hollow fibers, the present sensor is made of flat membranes. This new design is cheaper, smaller, and easier to use in comparison to the hollow fiber polymeric sensors. In order to test the sensor applicability, nitrogen and carbon dioxide were used as model gases. The effect of pressure on the response time and sensor accuracy was studied for the aforementioned gases. The response time (T_95%) of this low price sensor was 50?s, and the tolerance of measuring concentration was approximately 1.4% at 2?bar feed pressure. Also, increasing the feed pressure can improve the response time or accuracy of the sensor.     

Neutronic design investigation of a liquid injection-based second shutdown system for a typical research reactor using MCNPX

Safety systems, built on state-of-the-art technology, are essential for achieving acceptable levels of plant safety to minimize hazards to the reactor and the general public. The second shutdown system(SSS) as an engineered safety feature and a part of the reactor protection system(RPS) is a means for rapidly shutting down a nuclear reactor, keeping it in a subcritical state and serving as a backup to the first shutdown system(FSS). In this research, one SSS with two types of optimum chamber designs is proposed that take into account the main current characteristic features of the Tehran research reactor with improvements over earlier designs. They are based on a liquid neutron absorber injection that is preferably different, diverse, and independent from the FSS based on the rod drop mechanism. The major design characteristics of this SSS with two different chambers were investigated using MCNPX 2.6.0 code. The performed calculations showed that the designed SSS is a reliable shutdown system, assuring an appropriate shutdown margin and injection time, with no significant effects on the effective delayed neutron fraction while causing minimal variations to the core structure. Further, the reasonable financial cost and the prolongation of the operation cycle are additional advantages of this design.     

Quantitative automated inspection of standard parts using machine vision

On line automated visual inspection for quality and process control is becoming a very important requirement in an automated manufacturing environment. This paper examines the possibility of real-time inspection of standard part using machine vision.     

Efficacy of synbiotic supplementation in patients with nonalcoholic fatty liver disease: A systematic review and meta-analysis of clinical trials: Synbiotic supplementation and NAFLD

ABSTRACT

Objective: We systematically reviewed available randomized clinical trials (RCTs) to elucidate the overall effects of synbiotic supplementation in patients with nonalcoholic fatty liver disease (NAFLD).

Methods: PubMed, Scopus, ISI Web of science and Google Scholar were searched up to December, 2017. All RCTs using synbiotic supplements to treat NAFLD included in this systematic review and meta-analysis. Mean Difference (MD) was pooled using a random-effects model.

Results: Eleven eligible databases from seven RCTs were identified for the present meta-analysis. Our results showed that synbiotic supplementation can decrease body weight, fasting blood sugar, insulin, low density lipoprotein cholesterol, total cholesterol, triglyceride, high-sensitivity C-reactive protein, tumor necrosis factor alpha, alanine transaminase and aspartate transaminase levels among patients with NAFLD. In contrast, synbiotic did not have favorable effects on body mass index (BMI), waist circumference, homeostasis model assessment for insulin resistance (HOMA-IR), and high density lipoprotein cholesterol (HDL) levels compared with the placebo group.

Conclusion: The current study revealed that synbiotic supplementation has favorable effect on inflammatory factors, liver enzymes and some anthropometric indices, lipid profiles and glucose homeostasis parameters in patients with NAFLD.