A review on microalgal growth stress parameters for sustainable biofuel production

Clean Technologies and Environmental Policy - Rapid growth and high carbon-fixation properties make microalgal biomass a preferred source of energy-production technologies, particularly biodiesel...     

Condition monitoring of speed controlled induction motors using wavelet packets and discriminant analysis

This work presents an intelligent method for the condition monitoring of induction motors supplied with adjustable speed drives (ASD). Most of the previous work in this area concentrated on the fault detection and classification of induction motors supplied directly from an a.c. line. However, ASD driven induction motors are widely used in industrial processes and therefore obtaining an intelligent tool for the condition monitoring of these motors is necessary in terms of preventive maintenance and reducing down time due to motor faults. Here 3-phase supply side current of the ASD driving an induction motor is used to extract statistical features of wavelet packet decomposition coefficients within a frequency range of interest. This way, the information regarding the output frequency of the ASD and hence the motor speed is not required. Six identical three-phase induction motors were used for the experimental verification of the proposed method. One healthy machine was used as a reference, while other five with various synthetic faults were used for condition detection and classification. Extracted features obtained from decomposition coefficients of different wavelet filter types for all motors were employed in three different and popular classifiers. The proposed method and the performance of the features used for fault detection and classification are examined at various motor loads and speed levels, and it is shown that a successful condition monitoring system for induction motors supplied with ASDs is developed. The effect of selected filter type in wavelet decomposition to the condition monitoring process is analyzed and presented.     

Effects of polyethyleneimine adsorption on rheology of bentonite suspensions

The influence of the cationic polymer, polyethyleneimine polymer (PEI) on the flow behaviour of bentonite suspensions (2%, w/w), was studied. XRD, zeta potential and adsorption studies were done together with rheological measurements. The addition of PEI at concentration ranges of 10^-5-4.5 g/l and their rheological properties and stability of bentonite suspensions were studied. The adsorption rates for the bentonite suspensions are very fast. The XRD results showed that the PEG molecules did not intercalate into the layers of the clay.     

Effect of Sn Alloying on the Diffusion Bonding Behavior of Al-Mg-Si Alloys

Effect of Sn as an alloying element on the diffusion-bonding behavior of Al-Mg-Si alloy has been studied by means of differential scanning calorimetry (DSC), X-ray diffraction (XRD), scanning electron microscopy (SEM) and mechanical testing of the diffusion-bonded joint. XRD results revealed the formation of Mg₂Sn and (Sn) phases during solidification following induction casting. DSC results showed local liquid (Sn) formation during the bonding process for Sn-containing alloys, where its amount was found to be increasing with the increasing Sn content. Results revealed that Sn addition leads to an increase in the bond shear strength of the diffusion-bonded joints and elimination of the irregularities formed on the bonded interface. Fractured surfaces showed that formation of (Sn) layer at the bonded interface causes the fracture to transform from the ductile to the mixed fracture mode.     

Delivery of Metabolically Neuroactive Probiotics to the Human Gut

The human microbiome is a rich factory for metabolite production and emerging data has led to the concept that orally administered microbial strains can synthesize metabolites with neuroactive potential. Recent research from ex vivo and murine models suggests translational potential for microbes to regulate anxiety and depression through the gut-brain axis. However, so far, less emphasis has been placed on the selection of specific microbial strains known to produce the required key metabolites and the formulation in which microbial compositions are delivered to the gut. Here, we describe a double-capsule technology to deliver high numbers of metabolically active cells derived from the 24-strain probiotic product SH-DS01 to the gastrointestinal tract, including the small intestine, where immune responses and adsorption of metabolites into the bloodstream occur. Based on its genome sequence, Limosilactobacillus reuteri SD-LRE2-IT was predicted to have the genetic capacity to de novo produce a specific metabolite of interest to brain health, vitamin B12, which could be confirmed in vitro. Taken together, our data conceptualizes the importance of rationally defined microbial strain characterization based on genomics and metabolomics data, combined with carefully designed capsule technology for delivery of live cells and concomitant functionality in and beyond the gut ecosystem.     

EGFR-Targeted Pentacyclic Triterpene Analogues for Glioma Therapy

Glioma, particularly its most malignant form, glioblastoma multiforme (GBM), is the most common and aggressive malignant central nervous system tumor. The drawbacks of the current chemotherapy for GBM have aroused curiosity in the search for targeted therapies. Aberrantly overexpressed epidermal growth factor receptor (EGFR) in GBM results in poor prognosis, low survival rates, poor responses to therapy and recurrence, and therefore EGFR-targeted therapy stands out as a promising approach for the treatment of gliomas. In this context, a series of pentacyclic triterpene analogues were subjected to in vitro and in silico assays, which were conducted to assess their potency as EGFR-targeted anti-glioma agents. In particular, compound 10 was the most potent anti-glioma agent with an IC₅₀ value of 5.82 µM towards U251 human glioblastoma cells. Taking into account its low cytotoxicity to peripheral blood mononuclear cells (PBMCs), compound 10 exerts selective antitumor action towards Jurkat human leukemic T-cells. This compound also induced apoptosis and inhibited EGFR with an IC₅₀ value of 9.43 µM compared to erlotinib (IC₅₀ = 0.06 µM). Based on in vitro and in silico data, compound 10 stands out as a potential orally bioavailable EGFR-targeted anti-glioma agent endowed with the ability to cross the blood–brain barrier (BBB).     

Energy and exergy analyses of a raw mill in a cement production

Cement production has been one of the most energy intensive industries in the world. In order to produce raw materials preparation, clinker and rotary kilns are widely used in cement plants. The objective of this study is to perform energy and exergy analysis of a raw mill (RM) and raw materials preparation unit in a cement plant in Turkey using the actual operational data. The RM has a capacity of 82.9 ton-material hourly. Both energy and exergy efficiencies of the RM are investigated for the plant performance analysis and improvement, and are determined to be 84.3% and 25.2%, respectively. The present technique is proposed as a useful tool in the analysis of energy and exergy utilization, developing energy policies and providing energy conservation measures.     

Temperature dependence of copper,iron, nickel and chromium transfers into various black and green tea infusions

Transfer ratios of copper, iron, nickel and chromium from 10 blended, unblended, instant and green tea samples of Turkish or British origin into the infusions have been determined at different brewing temperatures (18, 40, 60 and 80°C). The transfer ratio of each metal into the infusion appeared to be dependent on both temperature and strength of infusions as well as the kind of tea. Ingested metal amounts were calculated and discussed. © 1998 SCI.     

Liquid diffusion model for drying a stack of rough rice

Drying of a stack of rough rice was experimentally and theoretically investigated. Stacks of rough rice having different heights were dried with forced convection of warm air. A theoretical model was developed for predicting the bulk drying kinetics of a stack of rough rice using the analytical solution of liquid diffusion equation based on Fick's law. Effective diffusion coefficients were obtained minimizing the sum of squared differences between the theoretical results and experimental data obtained for various drying conditions. Drying air temperature is the most effective factor on the total rate of moisture removal from the stack. The bulk drying rate of a stack of rough rice was considerably reduced as compared to that of a single layer as the height of the stack increased. Agreement between the theoretical and experimental result is very good. Copyright © 2003 John Wiley & Sons, Ltd.