Formation of acrylamide in microwave-roasted sorghum and associated dietary risk

The effect of microwave roasting parameters (300, 450 and 600 W; 5, 10 and 15 min) on acrylamide content in sorghum grain was determined using High Pressure Liquid Chromatography (HPLC)-photo diode array (PDA) detector coupled with C-18 column. Samples roasted at 300 and 450 W did not possess acrylamide, whereas 600 W (15 min) favoured formation of 2740.19 µg/kg of acrylamide, levels far exceeding the defined European Union (EU) limits. The chronic daily intake (CDI) for acrylamide through consumption of such grain flour was 3.25–9.5-fold higher to Joint FAO/WHO Expert Committee on Food Additives (JECFA) defined high exposure limits. The margin of exposure (MOE) values ranged from 4.3 to 12.76 and from 11.07 to 32.27 for neoplastic and neurological effects, respectively, demonstrating high exposure and serious health concerns associated with dietary intake of this toxicant. This study assesses the risk for the Indian population and highlights the importance of optimising process parameters for food product to minimise such exposure risks.     

Scientific basis for establishing country greenhouse gas estimates for rice-based agriculture: An Indian case study

A comprehensive scientific assessment of CH₄ budget estimation for Indian rice paddies, based on a decade of measurements in India, is presented. Indian paddy cultivation areas contain soils that have low to medium levels of soil organic carbon. The average seasonally integrated CH₄ flux (E _sif) values calculated from these measurements were 15.3 ± 2.6 g m^–2 for continuously flooded (CF), 6.9 ± 4.3 g m^–2 for intermittently flooded (IF) single aeration (SA) and 2.2 ± 1.5 g m^–2 for IF multiple aeration (MA) rice ecosystems. For CF and IF (MA) rice ecosystems having high soil organic carbon, without organic amendments, the CH₄ flux (E _sif) may be increased by 1.7 times relative to low soil organic carbon, whereas it may enhance by 5.3 for CF if amended organically. Organic amendment and high soil organic carbon paddy areas do not alter the methane budget estimates for India (3.6±1.4 TgY^–1) much, due to their small paddy harvested area. Methane estimated using average emission factors (E _sif) for all paddy water regimes, which include harvested areas having soils with high organic carbon and organic amendments, may give a budget of 5 TgY^–1 for India.     

Evaluation of Grid-Connected Photovoltaic Plants Based on Clustering Methods

Photovoltaic (PV) systems are electric power systems designed to supply usable solar power by means of photovoltaics, which is the conversion of light into electricity using semiconducting materials. PV systems have gained much attention and are a very attractive energy resource nowadays. The substantial advantage of PV systems is the usage of the most abundant and free energy from the sun. PV systems play an important role in reducing feeder losses, improving voltage profiles and providing ancillary services to local loads. However, large PV grid-connected systems may have a destructive impact on the stability of the electric grid. This is due to the fluctuations of the output AC power generated from the PV systems according to the variations in the solar energy levels. Thus, the electrical distribution system with high penetration of PV systems is subject to performance degradation and instabilities. For that, this project attempts to enhance the integration process of PV systems into electrical grids by analyzing the impact of installing grid-connected PV plants. To accomplish this, an indicative representation of solar irradiation datasets is used for planning and power flow studies of the electric network prior to PV systems installation. Those datasets contain lengthy historical observations of solar energy data, that requires extensive analysis and simulations. To overcome that the lengthy historical datasets are reduced and clustered while preserving the original data characteristics. The resultant clusters can be utilized in the planning stage and simulation studies. Accordingly, studies related to PV systems integration into the electric grid are conducted in an efficient manner, avoiding computing resources and processing times with easier and practical implementation.     

Optimization of process parameters affecting surface roughness in magnetic abrasive finishing process

Development in manufacturing technology enhances the mechanical behavior of machined parts and improves the surface finish with high precision, which conveys the progressive importance of magnetic abrasive finishing (MAF) process. In current research work, magnetic abrasive particles were used as finishing tools during the MAF process. However, these magnetic abrasives are fabricated by special techniques, i.e., the adhesive bonding-based method, the sintering method, the plasma-based method and so on. The present study explores the basic finishing characteristics of the magnetic abrasive produced by the sintering process. After the sintering process, improved quality of magnetic abrasives was obtained, where the abrasive particle sticks on the base metal matrix. The abrasive particle used is alumina powder and the magnetic particle is iron powder. Experiments were performed on Stainless Steel 202 to inspect the sound effects of several process parameters such as rotational speed, electromagnet voltage, machining gap and abrasive particle size on machining performance. Apart from that, surface roughness was also measured, which revealed the influence of the abrasive particle on the machined surface in terms of surface finish. It is observed from this study that appropriate size of magnetic abrasive particle optimizes the surface finish.     

Decomposition-based design optimization method using genetic co-evolution

The paper examines new strategies for the implementation of genetic algorithms in a decomposition-based approach for design. In this approach, the design problem is decomposed into smaller-sized sub-problems, the solutions for which are obtained through co-evolution. The emphasis resides in evaluating methods for exchanging design information relevant to coordinating solutions of temporarily decoupled sub-problems. Methods based on modification of genetic makeup through experiential inheritance (exposure to another species), and through inter-species migration are investigated in this work. Different forms of design problem coupling are investigated, ranging from coupling through constraints only, to coupled objective and constraint functions. The proposed strategies are validated through implementation in representative algebraic and structural design problems.     

Adaptive Discretization for Computerized Tomography

Two adaptive discretization frameworks are tested for computerized tomography (CT) data reconstruction. Removal of inactive pixels is primary motivation. Efficient and user independent entropy optimized masking is employed for spatial filtering purposes. Density of nodes at high gradient of reconstructed physical property is used as adaptation criterion. An alternative option, independent from noisy projection data and nature of the physical properties, is also discussed. Sensitivity analysis between the uniform and nonuniform (evolved via adaptive route) reconstruction grid reveals the utility of nonuniform grids. Iterative and transform based reconstruction techniques are used. Outcomes are tested successfully on three real world projection data from two different compact CT setups and one commercial high-resolution micro-CT scanner.     

Comparison of urea clearance in low‐efficiency low‐flux vs. high‐efficiency high‐flux dialyzer membrane with reduced blood and dialysate flow: An in vitro analysis

Rapid removal of small molecules during hemodialysis places an acutely ill patient with kidney failure at an increased risk of hemodynamic instability and for dialysis disequilibrium syndrome. The use of high‐flux, high‐efficiency (HEF) dialyzers may increase this risk despite reductions in blood and dialysate flow. We performed in vitro experiments to compare urea clearance at low dialysate flow and various blood flows using a low‐efficiency low‐flux (LEF) and a HEF membrane. Compared to LEF, there was a significant increase in the clearance of urea at all blood flows with the HEF (all P values < 0.005). HEF dialyzer (F180NR) had higher urea clearance at a blood flow of 150 mL/min than LEF dialyzer (F5) at blood flow of 300 mL/min (144.1 ± 0.99 vs. 130.1 ± 0.001 mL/min for F180 vs. F5, respectively, P < 0.002). Our data suggest that use of HEF dialyzer are not as safe as LEF in high‐risk acute dialysis patients since these are associated with more rapid removal of urea despite reduction in blood and dialysate flow as compared to LEF.     

A ROBUST MART ALGORITHM FOR TOMOGRAPHIC APPLICATIONS

The present work is concerned with the development of a robust reconstruction algorithm for applications involving tomography. In an earlier study it was shown that among the ART family of algorithms, the multiplicative algebraic reconstruction algorithm (MART) was the most appropriate for tomographic reconstruction [1]. In the present work, the MART algorithm has been extended so that (a) its performance is now acceptable over a wider range of relaxation factors, (b) the time requirement for convergence to a solution is lower, and (c) its performance is less sensitive to noise in the projection data. Applications considered for evaluating the proposed algorithms are (1) a circular region with holes, (2) a three-dimensional temperature field in a differentially heated fluid layer, and (3) experimental data recorded in a differentially heated fluid layer using an interferometer. The proposed algorithms are seen to be an improvement over those presently available, for all three examples considered.