A set theoretical shuffled shepherd optimization algorithm for optimal design of cantilever retaining wall structures

Engineering with Computers - In this paper, a recently developed meta-heuristic algorithm, shuffled shepherd optimization algorithm (SSOA), is employed for optimal design of reinforced concrete...     

Energy inputs and crop yield relationship in potato production in Hamadan province of Iran

The aim of this study was to determine energy consumption and the relationship between energy input and yield for potato production in Kaboud Rahang region of Hamadan state. The data used in this study are collected by questionnaire. The results revealed that nitrogen fertilizer (39%), diesel (21%), seed (14.9%), water (7.5%) and manure (6.4%) consumed the bulk of energy. In the surveyed farms, average yield and energy consumption were calculated as around 28613.7 kg/ha, 92296.3 MJ/ha, respectively. The results also showed that energy ratio, specific energy and energy productivity were 1.1, 3.2 MJ/kg and 0.3 kg/MJ, respectively. An econometric model was developed to estimate the impact of energy inputs on yield by using parametric methods. For this purpose, potato yield, an endogenous variable was assumed to be a function of energy inputs: fertilizer manure, chemical, machinery, human, water for irrigation, diesel and seed. The empirical results indicated that variables: fertilizer, chemical, seed and human were found statistically significant and contributed to yield. Among statistically significant exogenous variables, seed, water for irrigation, chemical, human and fertilizer were ranked in terms of elasticities.     

N ‐acetylcysteine–PLGA nano‐conjugate: effects on cellular toxicity and uptake of gadopentate dimeglumine

Gadolinium as a contrast agent in MRI technique combined with DTPA causes contrast induced nephropathy (CIN) and nephrogenic systemic fibrosis (NSF) which can reduce by usage of antioxidants such as N‐acetyl cysteine by increasing the membrane''s permeability leads to lower cytotoxicity. In this study, N ‐acetyl cysteine‐PLGA Nano‐conjugate was synthesized according to stoichiometric rules of molar ratios andafter assessment by FTIR, NMR spectroscopy and Atomic Force Microscopy (AFM) imaging was combined with Magnevist® (gadopentetate dimeglumine) and its effects on the renal cells were evaluated. MTT [3‐(4,5‐Dimethylthiazol‐2‐yl)‐2,5‐Diphenyltetrazolium Bromide] and cellular uptake assays have indicated relatively significant toxicity of magnevist (P  < 0.05) on three cell lines including HEK293, MCF7 and L929 compared to other synthesized ligands that shown no toxicity. Moreover, systemic evaluation has shown no notable changes of blood urea nitrogen (BUN) and creatinine in kidney of mice. In consequence, antioxidant effect was increased as well as the renal toxicity of the contrast agent reduced at the cell level. As a result, PLGA‐NAC nano‐conjugate can be a promising choice for decreasing the magnevist toxicity for treatment and prevention of CIN and will be able to open a new horizon to research on reduction of toxicity of contrast agents by using nanoparticles.Inspec keywords: blood, toxicology, nanofabrication, cellular biophysics, biomedical materials, nanoparticles, chromatography, cancer, biodegradable materials, biomedical MRI, kidney, pH, nanomedicine, patient treatment, diseases, atomic force microscopy, Fourier transform infrared spectraOther keywords: cellular toxicity, gadopentate dimeglumine, contrast agent, magnetic resonance imaging technique, diethylenetriamine pentaacetate, contrast‐induced nephropathy, nephrogenic systemic fibrosis, stoichiometric rules, molar ratios, dimethyl sulphoxide solution, chromatography techniques, nuclear magnetic resonance spectroscopy, atomic force microscopy imaging, Magnevist®, gadopentetate dimeglumine, renal cells, MTT cytotoxicity, human embryonic kidney‐293, L929 cell lines, in vitro conditions, cellular uptake assays, Magnevist uptake, antioxidant effect, renal toxicity, cell level, PLGA nanocarrier, acetylcysteine nanoconjugate, Magnevist toxicity, N‐acetylcysteine–PLGA nano‐conjugate, N‐acetyl cysteine‐poly‐lactic‐co‐glycolic acid nanoconjugate     

Microstructure, property and processing relation in gradient porous cathode of solid oxide fuel cells using statistical continuum mechanics

This paper investigates the relation between microstructure, macroscopic transport properties, and fabrication processing for a gradient porous cathode of solid oxide fuel cells (SOFCs). Functionally graded porous cathode with smooth variations in pore size is composed of lanthanum strontium manganite (LSM) fabricated on yttria stabilized zirconia (YSZ) electrolyte substrate using a multi-step spray pyrolysis (SP) technique at various deposition conditions. Two-dimensional (2D) serial-sections of the gradient porous microstructure obtained by FIB-SEM are fully characterized using statistical correlation functions. Results of statistical analysis of the microstructures revealed that the SP processing technique is capable of generating statistically identical and homogeneous microstructures with smooth gradient in pore size resulting from changing the processing parameters. Strong contrast statistical approach is also used to predict the in-plane temperature dependent effective electrical conductivity of the gradient porous cathode and the results are compared to the experimental data.     

On Modeling the Medical Care Insurance Data via a New Statistical Model

Proposing new statistical distributions which are more flexible than the existing distributions have become a recent trend in the practice of distribution theory. Actuaries often search for new and appropriate statistical models to address data related to financial and risk management problems. In the present study, an extension of the Lomax distribution is proposed via using the approach of the weighted T-X family of distributions. The mathematical properties along with the characterization of the new model via truncated moments are derived. The model parameters are estimated via a prominent approach called the maximum likelihood estimation method. A brief Monte Carlo simulation study to assess the performance of the model parameters is conducted. An application to medical care insurance data is provided to illustrate the potentials of the newly proposed extension of the Lomax distribution. The comparison of the proposed model is made with the (i) Two-parameter Lomax distribution, (ii) Three-parameter models called the half logistic Lomax and exponentiated Lomax distributions, and (iii) A four-parameter model called the Kumaraswamy Lomax distribution. The statistical analysis indicates that the proposed model performs better than the competitive models in analyzing data in financial and actuarial sciences.     

Updating stochastic model coefficients for prediction of arc furnace reactive power

The time varying nature of electric arc furnace (EAF) gives rise to voltage fluctuations which produce the effect known as flicker. The ability of static VAr compensator (SVC) in flicker reduction is limited by delays in thyristor ignition. To improve SVC performance in flicker compensation, EAF reactive power can be predicted for a half-cycle ahead, by using appropriate autoregressive moving average (ARMA) models. This paper uses huge field data collected from ac arc furnaces, and demonstrates that the EAF reactive power models coefficients are different from one data record to another and do not follow any specific law. Therefore, it is necessary to update the model coefficients for prediction purposes. For this purpose, two major adaptation algorithms, the least mean square (LMS) and recursive least square (RLS) are used to determine online the prediction relationship coefficients. By applying the methods to the data records and using some indices such as newly defined indices based on concepts of flicker frequencies and power spectral density, the transient and steady state performances of the methods are studied in EAF reactive power prediction. A simulation example on the application of the predictive models in a SVC control system is presented.     

Advances in chemical studies on low-molecular weight metabolites of marine fungi

The world oceans represent a resource of huge dimension, but their microbial diversity is still poorly understood. The chemistry of marine fungi was even a widely neglected part of natural product chemistry until recently. But symbiotic and epibiotic coexistence of fungi with higher forms of life, e.g. with sponges, forming highly specialised communities gave rise to an increasing interest in their secondary metabolism. More than 100 metabolites from marine fungi are known now, many of them showing fascinating structures or remarkable biological activities. This review gives a comprehensive summary of most structures and discusses their origin and properties.     

A comparative study of various intelligent based controllers for speed control of IPMSM drives in the field-weakening region

Precise speed control of an Interior Permanent Magnet Synchronous Motor (IPMSM) drive becomes a complex issue due to the nonlinear nature of its developed torque. The system nonlinearity becomes severe when the IPMSM drive operates in the field weakening region. In order to achieve perfect control characteristics, the main purpose of this paper is to present a detailed comparison of various intelligent based controllers for flux weakening speed control of an IPMSM drive. In this paper, the Brain Emotional Learning Based Intelligent Controller (BELBIC), Genetic-Fuzzy Logic Based Controller (GFLBC), as well as genetic-PI based controller, are considered. BELBIC is a computational model of emotional processing mechanism in the brain. The effectiveness of the proposed BELBIC controller-based IPMSM drive is verified by simulation results at different operating conditions. Moreover, control regimes such as Maximum Torque Per Ampere (MTPA) control and flux weakening (FW) control as well as voltage and current constraints have been successfully applied. The results prove BELBIC’s perfect control characteristics, such as fast and smooth speed response, low maximum starting current, adaptability to speed and load changes and robustness to parameter variations, disturbance and sudden one-phase interruption.     

Energy use patterns and econometric models of grape production in Hamadan province of Iran

This paper examines the energy use patterns and relationship between energy input and yield for grape production in Malayer region of Hamadan Province. Data from 50 farmers were collected using a face-to-face questionnaire method. In the surveyed vineyards, average yield and energy consumption were calculated as 18,530 kgha⁻¹ and 45,213.66 MJha⁻¹, respectively. Among input energy sources, fertilizers, electricity and farmyard manure contained highest energy shares with 37.25%, 19%, and 17.84%, respectively. The energy ratio and energy productivity were found to be 4.95 and 0.42 kgMJ⁻¹.Three econometric models were developed to estimate the impact of energy inputs on yield. The results revealed that impact of chemical, fertilizer and water on yield were significant at 1% probability level. Also, indirect and non-renewable energies were found to be rather high. Sensitivity analysis indicated that among the inputs, chemical has the highest MPP value of energy inputs. RTS (returns to scale) values for grape yield was found to be 2.15; thus, there prevailed an IRS of grape for estimated model. The net return was found to be positive as 2810.56 $ha⁻¹ for grape. The benefit-cost ratio was calculated as 2.08.