Studies on Egyptian cottonseeds: fatty acid-composition and protein patterns

Fourteen Egyptian cottonseed varieties were analysed to study some properties of their lipids and proteins. Lipid contents of the kernels ranged from 29.0 to 35.1%. The mean value of the iodine number was 110.9. The tested varieties showed little or no differences regarding to their fatty acid content. A slight higher proportion of linoleic acid was recorded for the triglycerides whereas the polar lipids components contained a lower amount of this fatty acids compared to that found in the total lipids. Protein contents in the examined varieties ranged from 32.3 to 37.9%. The amount of water-soluble protein ranged from 12.8 to 23.0% of the total protein. An almost complete recovery (94.5-100%) of the total protein was yielded when the extraction was performed with 0.02 N NaOH instead of water. The electrophoretic patterns of the water-soluble proteins gave only two bands, having a molecular weight between 14,000 and 25,000 dalton. A clear differentiation between the varieties was noticed when the alkaline soluble protein extracts were subjected to electrophoresis. Accordingly, the examined varieties were classified into five groups each of them having a similar spectrum.     

Optothermomechanical device for the interferometric characterization of fibers

An optothermomechanical (OTM) device was designed and constructed for fiber characterization with a double‐beam interference microscope. This device enabled us to correlate both the mechanical properties and the thermal properties with the optical properties of fibers. The OTM device consisted of three parts, which were used for the drawing (stress–strain), cooling, and heating of the fibers. The designed OTM device (cooling and heating) was attached to the Pluta microscope for the determination of the optical properties of high‐density polyethylene (PE) fibers at different temperatures (0–50°C). Also, this OTM device (drawing and heating), connected to the Pluta microscope, was used to study the influence of the temperature (10–50°C) and draw ratio (1–7) simultaneously on the optical properties of polypropylene (PP) fibers. Microinterferograms were provided for illustration. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 95: 647–658, 2005     

Design and optimization of MEMS based piezoelectric actuator for drug delivery systems

In this paper, piezoelectric principle based an actuator is design for a micropump, which is suitable for drug delivery systems. The natural frequency and stress analysis have been performed to determine the reliability of the device in terms of minimum safety factor. We have observed the uniform deflections of the actuators by varying the thicknesses of the piezoelectric layer of the actuator. The design of the actuators is considered in circular and rectangular geometry. The materials are selected appropriately such that the component is biocompatible and can be used in biomedical applications. Among the various considerations made on dimensions and geometry, it is observed that the circular piezoelectric actuator undergoes a high displacement of 2950 μm at an infinitesimal thickness of 0.1 μm. At minimum safety factor of one, the maximum stress and voltage the actuator can hold is 596 GPa and 8500 V respectively.

     

Time series classification with feature covariance matrices

In this work, a novel approach utilizing feature covariance matrices is proposed for time series classification. In order to adapt the feature covariance matrices into time series classification problem, a feature vector is defined for each point in a time series. The feature vector comprises local and global information such as value, derivative, rank, deviation from the mean, the time index of the point and cumulative sum up to the point. Extracted feature vectors for the time instances are concatenated to construct feature matrices for the overlapping subsequences. Covariances of the feature matrices are used to describe the subsequences. Our main purpose in this work is to introduce and evaluate the feature covariance representation for time series classification. Therefore, in classification stage, firstly, 1-NN classifier is utilized. After showing the effectiveness of the representation with 1-NN classifier, the experiments are repeated with SVM classifier. The other novelty in this work is that a novel distance measure is introduced for time series by feature covariance matrix representation. Conducted experiments on UCR time series datasets show that the proposed method mostly outperforms the well-known methods such as DTW, shapelet transform and other state-of-the-art techniques.     

Impact of spare parts remanufacturing on the operation and maintenance performance of offshore wind turbines: a multi-agent approach

Offshore wind farms are a growing source of energy, which aims to ensure a clean energy with a low environmental impact. In this context, this paper investigates opportunities of the turbine gearbox end of life-cycle to improve the operation and maintenance strategies. We determine the impact of spare part policy based on the remanufacturing of gearboxes recovered after each replacement. The remanufacturing implementation allows the extension of the gearbox life-cycle and involves a perfect organization and coordination between maintenance, monitoring, operation and spare part supply chain to determine the best way to use each gearbox of each wind turbine. In this paper, we present a multi-agent based approach to analyze the impact of the spare parts remanufacturing strategy on the performance of an offshore wind farm in term of total cost and carbon footprint.     

Multi-walled carbon nanotube supported aminomethylphosphine-Ru(II) complexes: Optical behavior and catalytic properties in transfer hydrogenation of acetophenone derivatives

The novel multi-walled carbon nanotube (MWCNT) supported bis(diphenylphosphinomethyl)amine [MWCNT@CHO-NHArN(CH₂PPh₂)₂ type] ligands and their Ru(II) complexes have been synthesized and characterized with Fourier Transform Infrared Spectrometry (FT-IR), Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray (EDX), Transmission Electron Microscopy (TEM), Ultraviolet-Visible Spectrometry, X-Ray Diffraction Spectrometry (XRD), and Thermal analysis (TG/DTA) techniques. In addition, MWCNT@CHO-NHArN(CH₂PPh₂)₂Ru(p-cymene)Cl₂ type complexes were tried as catalysts in the catalytic transfer hydrogenation reactions of acetophenone derivatives. The crystallite size and lattice strain of the MWCNT-based compounds were calculated by the Scherrer's equation. The optical parameters of the MWCNT-based structures were analyzed and the band gap enhanced from 4.42 eV to 4.98 eV. It was confirmed that the reduction of bromo and chloro acetophenone derivatives using all the catalysts, the conversions were high. The results showed that MWCNT-supported Ru(II) complexes were efficient catalysts in the reduction of bromo and chloro acetophenone derivatives with 99% efficiency in K₂CO₃ media at 80 ^°C.     

Bayesian Belief Network Used in the Chemical and Process Industry: A Review and Application

With the increasing growth of the chemical and process industries, it is necessary to ensure the safe operation of their complex and often hazardous installations, given their proximity to residential areas. Several techniques, such as fault tree analysis (FTA), bow-tie analysis (BTA), and Bayesian belief networks (BBNs), have been developed for adequate probabilistic risk assessment and management. The current work is aimed at performing a brief statistical review of the use of Bayesian networks in the chemical and process industry within the last decade. The review reveals that Bayesian networks have been used extensively in various forms of safety and risk assessment. This trend is attributable to the complexity of the installations found in this industry and the ability of BBN to intuitively represent these complexities, handle uncertainties, and update event probabilities. The paper is concluded with an illustrative example of the use of BBN to investigate the effectiveness of the safety barriers of a gas facility.

     

Adsorption kinetics and surface modeling of aqueous methylene blue onto activated carbonaceous wood sawdust

In this work, Sawdust was used to develop a new low-cost adsorbent and study its application to remove methylene blue dye from aqueous solution. Sawdust was calcined under air atmosphere at three different temperatures (300°C, 400°C, and 500°C) using phosphoric acid (H₃PO₄) as an activating agent. The structure, morphology, surface functions and the chemical composition of adsorbent were characterized by Fourier Transform Infrared spectra (FTIR), X-ray fluorescence (XRF), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), specific surface area (BET) and Boehm method. Different operational parameters such as pH, adsorbent loading, contact time and were investigated to evaluate experimental data. The adsorption of MB on SD-300, SD-400, and SD-500 show that the pseudo-second-order and Langmuir models fitted better the experimental results of MB adsorption onto all adsorbents. The maximum capacities based on the Langmuir model were 416.7 mg.g^?1 for SD-300, 526.3 mg.g^?1 for SD-400, and 819.7 mg.g^?1 for SD-500. The positive values of ΔG, ΔH, and ΔS implied that the adsorption process was non-spontaneous and endothermic nature. Finally, Regeneration of the SD-500 was investigated and optimization was performed using CCD combined with RSM.     

Pincer Type Ditertiary Aminomethylphosphine–Pd(II) Complexes Supported on Multi-Walled Carbon Nanotube: Catalytic Properties in Heck C–C Coupling Reactions

Pincer type aminomethylphosphine–Pd(II) complexes supported on multi-walled carbon nanotube (MWCNT) have been synthesized and characterized using X-Ray diffraction spectrometry, scanning electron microscopy, thermal analysis, energy dispersive X-Ray, Fourier transform infrared spectrometry, transmission electron microscopy (TEM) and ultraviolet–visible spectrometry techniques. The novel complexes were tried as catalysts in Heck C–C coupling reactions. The crystallite size and lattice strain of the MWCNT based compounds were calculated by the Scherrer’s equation. The optical parameters of the MWCNT based structures were analyzed and the band gap enhanced from 4.42 to 4.98 eV. Different solvents (toluene, 1,4-diooxane, DMF and NMP) and bases (Et₃N, Na₂CO₃, NaOAc and K₂CO₃) were tried at different temperatures (80, 100 and 110 °C) in the cross-coupling of bromobenzene with styrene. The optimum yield was found in the presence of K₂CO₃, 110 °C in 1,4-dioxane solvent system.     

INTRODUCTION OF DYNAMICS TO AN APPROACH FOR BATCH PROCESS MONITORING USING INDEPENDENT COMPONENT ANALYSIS

Use of independent component analysis (ICA) in developing statistical monitoring charts for batch processes has been reported previously. This article extends the previous work by introducing time lag shifts to include process dynamics in the ICA model. Comparison of the dynamic ICA-based method with other batch process monitoring approaches based on static ICA, static principal component analysis (PCA), and dynamic PCA is made for an industrial batch polymerization reactor and a simulated fed-batch penicillin fermentation process. For both case studies, it was found that the dynamic ICA approach detected faults earlier than other approaches, with less ambiguity, and was the only approach that detected all the faults.