Effect of Mg2+-Fe3+ replacement on physical and electrical properties of the system MgxZn0.3Fe2.7−xO4±δ

X-ray analysis and d.c. electrical resistivity have been studied for the system Mg _x Zn_0.3Fe_2.7–x O_4± . The apparent density, X-ray density and porosity were also studied. It was found that the lattice parameter is independent of the substitution of iron ions with magnesium ions. Density, X-ray density and porosity do depend on replacement of the iron ions by magnesium ions. Two regions of resistivity were found; one region indicates the p-type and another one the n-type. This behaviour depends on the excess or deficiency and type of valency of the iron ions in the composition.     

Influence of dietary long-chain PUFA on premature baboon lung FA and dipalmitoyl PC composition

One of the major survival challenges of premature birth is production of lung surfactant. The lipid component of surfactant, dipalmitoyl PC (DPPC), increases in concentration in the period before normal term birth via a net shift in FA composition away from unsaturates. We investigated the influence of dietary DHA and arachidonic acid (AA) on lung FA composition and DPPC concentration in term and preterm baboons. Pregnant animals/neonates were randomized to one of four groups: breast-fed (B), term formula-fed (T⁻), preterm formulafed (P⁻), and preterm fed formula supplemented with DHA-AA (P⁺). Breast milk contained 0.68%wt DHA and the P⁺ group formula contained 0.61%wt DHA. In the preterm groups (P⁻ and P⁺), pregnant females received a course of antenatal corticosteroids. At the adjusted age of 4 wk, neonate lung tissue was harvested, and FA composition and DPPC were analyzed. Palmitate was ∼28%wt of lung total FA and no significant differences were found among the four treatment groups. In contrast, DPPC in the B group lung tissue was significantly greater than DPPC in the unsupplemented groups, but not compared with the P⁺ group. The B and P⁺ groups were not significantly different in DHA and AA, but were different compared with the unsupplemented (T, P⁻) groups. These results indicate that LCP supplementation increases lung DHA and AA, without compromising overall lung 16∶0 or DPPC. The shift in FA composition toward greater unsaturation in the groups consuming LCP supported improved surfactant lipid concentration in preterm neonate lungs.     

Augmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homes

With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26?% enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.

     

Optimal Machine Learning Enabled Performance Monitoring for Learning Management Systems

Learning Management System (LMS) is an application software that is used in automation, delivery, administration, tracking, and reporting of courses and programs in educational sector. The LMS which exploits machine learning (ML) has the ability of accessing user data and exploit it for improving the learning experience. The recently developed artificial intelligence (AI) and ML models helps to accomplish effective performance monitoring for LMS. Among the different processes involved in ML based LMS, feature selection and classification processes find beneficial. In this motivation, this study introduces Glowworm-based Feature Selection with Machine Learning Enabled Performance Monitoring (GSO-MFWELM) technique for LMS. The key objective of the proposed GSO-MFWELM technique is to effectually monitor the performance in LMS. The proposed GSO-MFWELM technique involves GSO-based feature selection technique to select the optimal features. Besides, Weighted Extreme Learning Machine (WELM) model is applied for classification process whereas the parameters involved in WELM model are optimally fine-tuned with the help of Mayfly Optimization (MFO) algorithm. The design of GSO and MFO techniques result in reduced computation complexity and improved classification performance. The presented GSO-MFWELM technique was validated for its performance against benchmark dataset and the results were inspected under several aspects. The simulation results established the supremacy of GSO-MFWELM technique over recent approaches with the maximum classification accuracy of 0.9589.     

Computational modeling of flow over an ogee spillway

This paper presents an investigation into the hydraulics of regular ogee-profile spillways. The free-surfaces of the fluid for several flow heads as measured in the hydraulics laboratory are used as benchmarks. The finite element computational fluid dynamics software, ADINA, was used to predict the free surface over an ogee spillway and thus model the flow field. Since the actual flow is turbulent the k-ε flow model was used. For the cases considered in this paper, ADINA predicted reasonable free surface results that are consistent with general flow characteristics over spillways. The results are also in close agreement with measured free-surface profiles over the entire length of the spillway.     

On the importance of specific interface area in clay nanocomposites of PMMA filled with synthetic nano-mica

In clay nanocomposites, the specific interface area is the key factor determining potential improvements of properties. Nevertheless, in most systematic studies of nanocomposites little emphasis is put on assuring and characterizing dispersion quality. To probe the influence of dispersion quality, we compare nanocomposites filled with two layered silicates which were made by melt compounding and solution blending, respectively. Poly(methyl methacrylate) (PMMA) is chosen here as a thermoplastic model matrix which was compounded with a synthetic nano-mica (O-hect) and commercial Bentone with typical diameters of 5–7 μm and <300 nm, respectively.     

A phase‑locked loop using ESO‑based loop flter for grid‑connected converter: performance analysis

An extended state observer (ESO)-based loop flter is designed for the phase-locked loop (PLL) involved in a disturbed gridconnected converter (GcC). This ESO-based design enhances the performances and robustness of the PLL, and, therefore, improves control performances of the disturbed GcCs. Besides, the ESO-based LF can be applied to PLLs with extra flters for abnormal grid conditions. The unbalanced grid is particularly taken into account for the performance analysis. A tuning approach based on the well-designed PI controller is discussed, which results in a fair comparison with conventional PItype PLLs. The frequency domain properties are quantitatively analysed with respect to the control stability and the noises rejection. The frequency domain analysis and simulation results suggest that the performances of the generated ESO-based controllers are comparable to those of the PI control at low frequency, while have better ability to attenuate high-frequency measurement noises. The phase margin decreases slightly, but remains acceptable. Finally, experimental tests are conducted with a hybrid power hardware-in-the-loop benchmark, in which balanced/unbalanced cases are both explored. The obtained results prove the efectiveness of ESO-based PLLs when applied to the disturbed GcC.     

A phase-locked loop using ESO-based loop filter for grid-connected converter:performance analysis

An extended state observer(ESO)-based loop filter is designed for the phase-locked loop(PLL)involved in a disturbed grid-connected converter(GcC).This ESO-based...     

Oxidative solution polymerization of aniline hydrochloride onto electrospun nanofibers mats of polylactic acid: Preparation method and characterization

In this work, we present the preparation of polylactic acid (PLLA)/polyaniline (PANI) conductive composite nanofibers mats. They are prepared by bulk oxidative solution polymerization of PANI onto electrospun non‐woven fibers mats of PLLA. The PANI ratio in the composite is about 70%w/w. Scanning electron microscopy (SEM) shows that PLLA nanofibers are randomly oriented, beads free with diameters of 186 ± 85 nm, The PLLA/PANI composite nanofibers diameter values are 518 ± 128 nm with a good adherence between PANI and PLLA nanofibers. DSC and XRD measurements reveal an amorphous structure of the electrospun PLLA fibers due to the rapid evaporization of the solvent. FTIR and UV–vis spectra reflect good mutual interactions between PANI and PLLA chains. The DC‐conductivities ( ) far better than other published ones for similar composites prepared by bulk oxidative solution polymerization of PANI onto other electrospun nanofiber mats or with electrospun nanofibers from a solution mixture of PLLA and PANI. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41618.