Effects of Additives on Thermal Decompositions of Carbon Black/High Density Polyethylene Compounds

In the present work, the effects of additives, including contents of the added antioxidants and type of the selected metallic stearates (either calcium stearate (CaSt) or zinc stearate (ZnSt)), on the thermal stabilities of carbon black (CB)/high density polyethylene (HDPE) compounds were studied. The results showed that the AO contents played a key role in the thermal stabilities of the CB/HDPE compounds — the higher the AO content, the higher the thermal stabilities. Although the CaSt-containing compounds were slightly superior to those with ZnSt in terms of the thermal stabilities, the remaining solid residue of CaSt after heated to the temperature of 600 °C (mainly calcium carbonate (CaCO3) as characterized by the X-ray diffraction (XRD) technique) seemed to catalyze the decomposition of CB in the HDPE-based compounds. Hence, the quantification of CB in the CaSt-containing compounds with a muffle furnace gave an inaccurate CB content — much lower than actual value. However, this phenomenon was negligible in the ZnSt-containing system.

Mine Production Index (MPI): New Method to Evaluate Effectiveness of Mining Machinery

OEE has been used in many industries as measure of performance. However due to limitations of original OEE, it has been modified by various researchers. OEE for mining application is special version of classic equation, carries these limitation over. In this paper it has been aimed to modify the OEE for mining application by introducing the weights to the elements of it and termed as Mine Production index (MPi). As a special application of new index MPishovel has been developed by authors. This can be used for evaluating the shovel effectiveness. Based on analysis, utilization followed by performance and availability were ranked in this order. To check the applicability of this index, a case study was done on four electrical and one hydraulic shovel in a Swedish mine. The results shows that MPishovel can evaluate production effectiveness of shovels and can determine effectiveness values in optimistic view compared to OEE. MPi with calculation not only give the effectiveness but also can predict which elements should be focused for improving the productivity.

Banana Peels as an Eco-Sorbent for Manganese Ions

This study was conducted to evaluate the manganese removal from aqueous solution using Banana peels activated carbon (BPAC). Batch experiments have been carried out to determine the influence of parameters such as pH, biosorbent dose, initial metal ion concentrations and contact times on the biosorption process. From these investigations, a significant increase in percentage removal of manganese 97.4% is observed at pH value 5.0, biosorbent dose 0.8 g, initial concentration 20 ppm, temperature 25 ± 2°C, stirring rate 200 rpm and contact time 2h. The equilibrium concentration and the adsorption capacity at equilibrium of the experimental results were fitted to the Langmuir and Freundlich isotherm models; the Langmuir isotherm was found to well represent the measured adsorption data implying BPAC had heterogeneous surface. A raw groundwater samples were collected from Baharmos groundwater treatment plant network at Embaba and Manshiet Elkanater City/District-Giza, Egypt, for treatment at the best conditions that reached at first phase by BPAC. The treatment with BPAC could reduce iron and manganese value of raw groundwater by 91.4% and 97.1%, respectively and the effect of the treatment process on the microbiological properties of groundwater sample showed decrease of total bacterial count either at 22°C or at 37°C to 85.7% and 82.4%, respectively. Also, BPAC was characterized using SEM and FTIR spectroscopy.

A New Method for Estimating the Mass Recession Rate for Ablator Systems

As the human race will continue to explore the space by creating new space transportation means and sending them to other planets, the enhance of atmospheric reentry study is crucial. In this context, an analysis of mass recession rate of ablative materials for thermal shields of reentry spacecrafts is important to be carried out. The paper describes a new estimation method for calculating the mass recession of an ablator system made of carbon fiber reinforced plastic materials. This method is based on Arrhenius equation for low temperatures and, for high temperatures, on a theory applied for the recession phenomenon of carbon fiber reinforced plastic materials, theory which takes into account the presence of the resin inside the materials. The space mission of USERS spacecraft is considered as a case study.

MPC of Single Phase Inverter for PV System

This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a full bridge (FB) voltage source inverter (VSI). No PI regulators to tune and carrier and modulating waves are required to produce switching sequence. Instead, the operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a three kW PV system at the input of UI-SPI in Matlab/Simulink. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Particle Size Effect on Shear Strength of Granular Materials in Direct Shear Test

The effect of particle size on shear strength of granular materials are investigated using direct shear tests. Small direct shear test (60 mm by 60 mm by 24 mm deep) were conducted for particles passing the sieves with opening size of 2.36 mm. Meanwhile, particles passing the standard 20 mm sieves were tested using large direct shear test (300 mm by 300 mm by 200 mm deep). The large direct shear tests and the small direct shear tests carried out using the same shearing rate of 0.09 mm/min and similar normal stresses of 100, 200 and 300 kPa. The results show that the peak and residual shear strength increases as particle size increases.

Raman Spectroscopy of Carbon Nanostructures in Strong Magnetic Field

One- and two-dimensional carbon nanostructures with sp2 hybridization of carbon atoms (single walled carbon nanotubes and graphene) are promising materials in future electronic and spintronics devices due to specific character of their electronic structure. In this paper we present a comparative study of graphene and single-wall carbon nanotubes by Raman spectro-microscopy in strong magnetic field. This unique method allows to study changes in electronic band structure of the two types of carbon nanostructures induced by a strong magnetic field.

Stabilization of Transition Metal Chromite Nanoparticles in Silica Matrix

This article presents summary on preparation and characterization of zinc, copper, cadmium and cobalt chromite nanocrystals, embedded in an amorphous silica matrix. The ZnCr2O4/SiO2, CuCr2O4/SiO2, CdCr2O4/SiO2 and CoCr2O4/SiO2 nanocomposites were prepared by a conventional sol-gel method under acid catalysis. Final heat treatment of the samples was carried out at temperatures in the range of 900−1200 ◦C to adjust the phase composition and the crystallite size, respectively. The resulting samples were characterized by Powder X-ray diffraction (PXRD), High Resolution Transmission Electron Microscopy (HRTEM), Raman/FTIR spectroscopy and magnetic measurements. Formation of the spinel phase was confirmed in all samples. The average size of the nanocrystals was determined from the PXRD data and by direct particle size observation on HRTEM; both results were correlated. The mean particle size (reviewed by HRTEM) was in the range from ∼4 to 46 nm. The results showed that the sol-gel method can be effectively used for preparation of the spinel chromite nanoparticles embedded in the silica matrix and the particle size is driven by the type of the cation A2+ in the spinel structure and the temperature of the final heat treatment. Magnetic properties of the nanocrystals were found to be just moderately modified in comparison to the bulk phases.

Evaluation of Short-Term Load Forecasting Techniques Applied for Smart Micro Grids

Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

3D Scaffolds Fabricated by Microfluidic Device for Rat Cardiomyocytes Observation

To mimic the natural circumstances of cell growth in an organism, we present three-dimensional (3D) scaffolds fabricated by microfluidics for cultivation. This work investigates the cellular behaviors of rat cardiomyocytes in gelatin 3D scaffolds compared to those on 2D control, such as proliferation, viability and morphology. We found that the scaffolds may induce skeletal differentiation of H9c2 cells.

Conversion of Jatropha curcas Oil to Ester Biolubricant Using Solid Catalyst Derived from Saltwater Clam Shell Waste (SCSW)

The discarded clam shell waste, fossil and edible oil as biolubricant feedstocks create environmental impacts and food chain dilemma, thus this work aims to circumvent these issues by using activated saltwater clam shell waste (SCSW) as solid catalyst for conversion of Jatropha curcas oil as non-edible sources to ester biolubricant. The characterization of solid catalyst was done by Differential Thermal Analysis-Thermo Gravimetric Analysis (DTATGA), X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Field Emission Scanning Electron Microscopy (FESEM) and Fourier Transformed Infrared Spectroscopy (FTIR) analysis. The calcined catalyst was used in the transesterification of Jatropha oil to methyl ester as the first step, and the second stage was involved the reaction of Jatropha methyl ester (JME) with trimethylolpropane (TMP) based on the various process parameters. The formated biolubricant was analyzed using the capillary column (DB-5HT) equipped Gas Chromatography (GC). The conversion results of Jatropha oil to ester biolubricant can be found nearly 96.66%, and the maximum distribution composition mainly contains 72.3% of triester (TE).

Study of TiO2 Nanoparticles as Lubricant Additive in Two-Axial Groove Journal Bearing

Load carrying capacity of an oil lubricated two-axial groove journal bearing is simulated by taking into account the viscosity variations in lubricant due to the addition of TiO2 nanoparticles as lubricant additive. Shear viscosities of TiO2 nanoparticle dispersions in oil are measured for various nanoparticle additive concentrations. The viscosity model derived from the experimental viscosities is employed in a modified Reynolds equation to obtain the pressure profiles and load carrying capacity of two-axial groove journal bearing. Results reveal an increase in load carrying capacity of bearings operating on nanoparticle dispersions as compared to plain oil.

Identification and Characterization of Heavy Metal Resistant Bacteria from the Klip River

Pollution of the Klip River has caused microorganisms inhabiting it to develop protective survival mechanisms. This study isolated and characterized the heavy metal resistant bacteria in the Klip River. Water and sediment samples were collected from six sites along the course of the river. The pH, turbidity, salinity, temperature and dissolved oxygen were measured in-situ. The concentrations of six heavy metals (Cd, Cu, Fe, Ni, Pb and Zn) of the water samples were determined by atomic absorption spectroscopy. Biochemical and antibiotic profiles of the isolates were assessed using the API 20E® and Kirby Bauer Method. Growth studies were carried out using spectrophotometric methods. The isolates were identified using 16SrDNA sequencing. The uppermost part of the Klip River with the lowest pH had the highest levels of heavy metals. Turbidity, salinity and specific conductivity increased measurably at Site 4 (Henley on Klip Weir). MIC tests showed that 16 isolates exhibited high iron and lead resistance. Antibiotic susceptibility tests revealed that the isolates exhibited multitolerances to drugs such as Tetracycline, Ampicillin, and Amoxicillin.

Method Development and Validation for the Determination of Cefixime in Pure and Commercial Dosage Forms by Specrophotometry

A simple, accurate and precise direct spectrophotometric method has been developed for the determination of cefixime in tablets and capsules. The method is based on the reaction of cefixime with a mixture of potassium iodide and potassium iodate to form yellow coloured product in ethanol-distilled water medium at room temperature which absorbed maximally at 352 nm. The factors affecting the reaction product were carefully studied and optimized. The validation parameters based on International Conference on Harmonisation (ICH, USA) guidelines were followed. The effect of common excipients used as additives has been tested and the tolerance limit was calculated for the determination of cefixime. Beer’s law is obeyed in the concentration range of 4 – 24 ug mL-1 with apparent molar absorptivity of 1.52 × 104 L mol-1cm-1 and Sandell’s sensitivity of 0.033 ug/cm2/ 0.001 absorbance unit. The limits of detection and quantitation for the proposed method are 0.32 and 1.06 ug mL-1, respectively. The proposed method has been successfully applied for the determination of cefixime in pharmaceutical formulations. The results obtained by the proposed method were statistically compared with the reference method using t- and F- values and found no significant difference between the two methods. The proposed method can be used as an alternate method for routine quality control analysis of cefixime in pharmaceutical formulations.

Thermal Expansion Coefficient and Young’s Modulus of Silica-Reinforced Epoxy Composite

In this study, the evaluation of thermal stability of the micrometer-sized silica particle reinforced epoxy composite was carried out through the measurement of thermal expansion coefficient and Young’s modulus of the specimens. For all the specimens in this study from the baseline to those containing 50 wt% silica filler, the thermal expansion coefficients and the Young’s moduli were gradually decreased down to 20% and increased up to 41%, respectively. The experimental results were compared with fillervolume- based simple empirical relations. The experimental results of thermal expansion coefficients correspond with those of Thomas’s model which is modified from the rule of mixture. However, the measured result for Young’s modulus tends to be increased slightly. The differences in increments of the moduli between experimental and numerical model data are quite large.

The Use of FBC Ash for Preparation of Types of Hydraulic Binders Similar to Portland Cement

The reduction of greenhouse gases emissions is highly discussed ecological theme at present. In addition to power industry also main production sectors of binders, i.e. cement, air and hydraulic lime are very sensitive to these questions. One of the possibilities how CO2 emissions can be reduced directly at clinker burnout is represented by partial substitution of lime with a material containing limy ions at absence of carbonate group. Fluidised fly ash is one of such potential raw materials where CaO can be found free and also bound in anhydrite, CaSO4. At application of FBC (fluidized bed combustion) fly ash with approximate 20% CaO content and its dosing ratio to high percent lime 1:2, corresponding stechiometrically to the preparation of raw material powder, approximately 0,37 t CO2 per 1 ton of one-component cement would be released at clinker burnout compared to 0,46 t CO2 when orthodox raw materials are used. The reduction of CO2 emissions thus could reach even 20%.

Physicochemical Analysis of Soxhlet Extracted Oils from Selected Northern Nigerian Seeds

The aim of the present study is to investigate the potential use of the selected seed oils. The oil was extracted using Soxhlet apparatus and the physicochemical characteristics of the oil determined using standard methods. The following results were obtained for the physicochemical parameters analysed: for Egusi seed oil, Oil yield 53.20%, Saponification value 178.03±1.25 mgKOH/g, Iodine value 49.10±0.32 g I2/100g, Acid value 4.30±0.86 mgKOH/g, and Peroxide value 5.80±0.27 meq/kg were obtained. For Pawpaw seed oil, Oil yield 40.10%, Saponification value 24.13±3.93 mgKOH/g, Iodine value 24.87±0.19 g I2/100g, Acid value 9.46±0.40 mgKOH/g, and Peroxide value 3.12±1.22 meq/kg were obtained. For Sweet orange seed oil, Oil yield 43.10%, Saponification value 106.30±2.37 mgKOH/g, Iodine value 37.08±0.04 g I2/100g, Acid value 7.59±0.77 mgKOH/g, and Peroxide value 2.21±0.46 meq/kg were obtained. From the obtained values of the determined parameters, the oils can be extracted from the three selected seeds in commercial quantities and that the egusi and sweet orange seed oils may be utilized in the industrial soap production.

Neural Networks for Distinguishing the Performance of Two Hip Joint Implants on the Basis of Hip Implant Side and Ground Reaction Force

In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

Comparative Analysis of Diverse Collection of Big Data Analytics Tools

Over the past era, there have been a lot of efforts and studies are carried out in growing proficient tools for performing various tasks in big data. Recently big data have gotten a lot of publicity for their good reasons. Due to the large and complex collection of datasets it is difficult to process on traditional data processing applications. This concern turns to be further mandatory for producing various tools in big data. Moreover, the main aim of big data analytics is to utilize the advanced analytic techniques besides very huge, different datasets which contain diverse sizes from terabytes to zettabytes and diverse types such as structured or unstructured and batch or streaming. Big data is useful for data sets where their size or type is away from the capability of traditional relational databases for capturing, managing and processing the data with low-latency. Thus the out coming challenges tend to the occurrence of powerful big data tools. In this survey, a various collection of big data tools are illustrated and also compared with the salient features.

A New Method to Estimate the Low Income Proportion: Monte Carlo Simulations

Estimation of a proportion has many applications in economics and social studies. A common application is the estimation of the low income proportion, which gives the proportion of people classified as poor into a population. In this paper, we present this poverty indicator and propose to use the logistic regression estimator for the problem of estimating the low income proportion. Various sampling designs are presented. Assuming a real data set obtained from the European Survey on Income and Living Conditions, Monte Carlo simulation studies are carried out to analyze the empirical performance of the logistic regression estimator under the various sampling designs considered in this paper. Results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the customary estimator under the various sampling designs considered in this paper. The stratified sampling design can also provide more accurate results.