Sulfonated Reduced Graphene Oxide (RGO-SO3H): As an Efficient Nanocatalyst for One-Pot Synthesis of 2-Amino-3-cyano-7-hydroxy-4H-chromenes Derivatives in Water

Sulfonated reduced graphene oxide (RGO-SO₃H) was found to be an efficient catalyst for one-pot synthesis of a class of 2-amino-3-cyano-7-hydroxy-4H-chromenes derivatives using multicomponent reaction (MCR) of phenols, aldehydes and malononitrile under mild and green conditions. The reaction was performed in water as a green solvent and range of 2-amino-3-cyano-7-hydroxy-4H-chromenes were obtained in good to excellent yields. The RGO-SO₃H was reusable at least 5 times without significant decrease in its catalytic activity.     

Design and implementation of tuned viscoelastic dampers for vibration control in milling

Passive means of vibration attenuation have been employed successfully and efficiently in machining systems such as turning and milling. Traditional approach to controlling vibration in a milling system is to develop control mechanisms for cutting tools or machine spindles. However, due to the nature of milling operations where the cutting tools rotate at high speed, the passive vibration control methods find very limited application with the traditional approach. In order to utilise the potential of the passive vibration control methodology in milling applications, the milling operation should be viewed as a system comprising an elastic structure and operation parameters. Dynamics of this closed-loop system should improve with improvement in dynamics of any of the system components, especially within the elastic structure that comprises the cutting tool, the machine tool, the workholding system and the workpiece. Although the level of improvement will vary depending on which component of the elastic chain is targeted for this purpose. This paper presents the development and testing of tuned viscoelastic dampers (TVDs) for vibration control through their application on a workpiece in milling operations. This work targets workpiece held on a palletised workholding system for the control of unwanted vibration and thus deviates from the traditional approach where cutting tool and/or machine spindles are targeted for vibration control strategies. Palletised workholding systems, due to their compact design, offer an opportunity to design passive damping mechanisms that are easier to implement in the case of a milling system. The TVD developed through this research is based on a commercially available viscoelastic damping polymer. Advantage of such materials is their high damping performance over a wide range of excitation frequencies. The TVD design process has used a unique combination of analytical modelling with experimental FRF data. Modal impact testing showed that the application of the TVD reduced the amplitude of vibration acceleration by 20 dB for the target mode. Since the target mode corresponded to torsional vibration, the TVD was effective in two planar coordinates, i.e. X and Y. In addition, the TVD also significantly reduced the amplitude of a vibration mode far from the mode it was designed for. The system has been tested experimentally to demonstrate significant reduction in vibration amplitudes during a milling process. The milling tests with different combinations of cutting parameters show that multi-TVD approach is always valid regardless of the parameters being used. The only requirement for TVDs to function effectively is that the natural frequency of the system, for which the TVDs are designed, is excited during the milling process.     

Thermal conductivity prediction of foods by Neural Network and Fuzzy (ANFIS) modeling techniques

A neuro-fuzzy modeling technique was used to predict the effective of thermal conductivity of various fruits and vegetables. A total of 676 data point was used to develop the neuro-fuzzy model considering the inputs as the fraction of water content, temperature and apparent porosity of food materials. The complexity of the data set which incorporates wide ranges of temperature (including those below freezing points) made it difficult for the data to be predicted by normal analytical and conventional models. However the adaptive neuro-fuzzy model (ANFIS) was able to predict conductivity values which closely matched the experimental values by providing lowest mean square error compared to multivariable regression and conventional artificial neural network (ANN) models. This method also alleviates the problem of determining the hidden structure of the neural network layer by trial and error.     

Analyzing and enhancing the parallel sort operation on multithreaded architectures

The sort operation is a core part of many critical applications (e.g., database management systems). Despite the large efforts to parallelize it, the fact that it suffers from high data-dependencies vastly limits its performance. Multithreaded architectures are emerging as the most demanding technology in leading-edge processors. These architectures include simultaneous multithreading, chip multiprocessors, and machines combining different multithreading technologies. In this paper, we analyze the memory behavior and improve the performance of the most recent parallel radix and quick integer sort algorithms on modern multithreaded architectures. We achieve speedups up to 4.69× for radix sort and up to 4.17× for quicksort on a machine with 4 multithreaded processors compared to single threaded versions, respectively. We find that since radix sort is CPU-intensive, it exhibits better results on chip multiprocessors where multiple CPUs are available. While quicksort is accomplishing speedups on all types of multithreading processers due to its ability to overlap memory miss latencies with other useful processing.     

Tree colonization trends on a sediment bar after a major flood

Tree mortality and regeneration in riparian areas are greatly influenced by flooding. The elevational distribution of Salix spp. and Robinia pseudoacacia were investigated by observing densities and standing conditions before and after a major flood on a sediment bar in the middle reaches of the Arakawa River in Kumagaya, Japan. The subsequent tree recruitment was also examined. R. pseudoacacia was easily washed away with the eroded sediment, whereas Salix spp. was found to be more tolerant. Both species were able to survive even after collapsing, provided that their roots were fully or partially embedded in the sediment. Re‐shooting of collapsed trees, rather than emergence from saplings (either by seeds or vegetative fragments), was observed to be the major method of recruitment after the flood. Therefore, tree density before the flood was unchanged, unless the trees were subject to washing away. Salix spp. recruitment was mainly observed in low‐lying areas and R. pseudoacacia in elevated areas. Recruitment from saplings was species‐specific. Salix spp. at high elevations originated mainly from shoot fragments as they need high levels of moisture for seed germination and at higher elevations, sediment moisture content is very low. R. pseudoacacia, on other hand, originated mainly from roots and seeds. At a given elevation, past recruitment patterns indicated that the annual recruitment of trees increased with tree density up to a particular threshold of recruitment density. Further increases in tree density beyond that optimum value resulted in a decline in recruitment. Furthermore, threshold density was observed to increase along with elevation for R. pseudoacacia while declining with Salix spp. Copyright © 2010 John Wiley & Sons, Ltd.     

Numerical treatment of nonlinear Emden–Fowler equation using stochastic technique

The article is based on the approximate solution of a well known Lane–Emden–Fowler (LEF) equation. A trial solution of the model is formulated as an artificial feed-forward neural network containing unknown weights which are optimized in an unsupervised way. The proposed scheme is tested successfully on various test cases of initial value problems of LEF equations. The reliability and effectiveness is validated through comprehensive statistical analysis.     

Surface functionalization of multi-walled carbon nanotubes via electron reduction of benzophenone by potassium metal

The covalent sidewall functionalization of multi-walled carbon nanotubes (MWCNTs) via the electron reduction of benzophenone by potassium metal is reported. Fourier transform infrared spectroscopy (FTIR) results show that diphenylcarbinol (DPC) groups were successfully grafted to the MWCNTs sidewalls after 10 days of reaction time. Raman and UV–vis spectroscopies reveal the presence of covalent sidewall functionalization. The percentage of residues for DPC-MWCNTs was found to be lower than that for pristine MWCNTs, which indicates the existence of functional groups on the sidewalls of DPC-MWCNTs. It is shown that the sidewall of the DPC-MWCNTs was covered by non-uniform layer of DPC, as observed by transmission electron microscopy (TEM). Results from Raman spectroscopy, FTIR, TGA, UV–vis spectroscopy and TEM confirm that the functionalization of the covalent sidewalls of MWCNTs was successfully performed by this method.     

Software Engineering Ethics in a Digital World

In ethics-aware software engineering, ethical considerations are explicitly taken into account across the software development life cycle and are an integral part of risk assessment and acceptance criteria.     

Purification and characterization of a novel glucoamylase from Fusarium solani

Thermostable enzymes are currently being investigated to improve industrial processes of starch saccharification. A novel glucoamylase was purified to electrophoretic homogeneity from the culture supernatant of Fusarium solani on a fast protein liquid chromatographic system (FPLC). The recovery of glucoamylase after gel filtration on FPLC was 31.8% with 26.2-fold increase in specific activity. The enzyme had a molecular mass of 40 kDa by SDS-PAGE and 41 kDa by gel filtration. The glucoamylase exhibited optimum activity at pH 4.5. The K_cat and K_m were 441/min and 1.9 mg/ml, respectively, for soluble starch, specificity constant (K_cat/K_m) was 232. The enzyme was thermally stable at 50 °C and retained 79% activity after 60 min at this temperature. The half-life of the enzyme was 26 min at 60°C. The enzyme was slightly stimulated by Cu²⁺ and Mg²⁺ and strongly inhibited by Hg²⁺, Pb²⁺, Zn²⁺, Ni²⁺ and Fe³⁺.     

Essential oil composition of commercial black tea (Camellia sinensis)

The essential oil components of different tea brands were investigated by gas chromatography. The oil yields of dried tea samples were ranged from 0.09% to 0.63%. Twenty-five compounds from Supreme and Lipton Yellow Label tea brands representing 98.0% and 88.0% of the Camellia sinensis oil were identified, respectively. The main ones were β-pinene (51.2%) and α-pinene (30.2%). Nineteen components from Tapal tea brand representing 76.7% of the C. sinensis oil were determined with high contents of muurol-5-en-4-a-ol (10.5%) and muurol-5-en-4-b-ol (31.3%). Fifteen components from Deer and Diana tea brands were identified, accounting for 83.3% and 78.2% of the oil containing α-cadinol and β-pinene. Seventeen components from non-branded teas were determined with high contents of muurol-5-en-4-a-ol and muurol-5-en-4-b-ol. Twenty-one compounds from non-branded Bangladeshi Shezan and Indian teas were also identified. All oils consisted of monoterpenic hydrocarbons, oxygenated monoterpenes and sesquiterpenes.