Modeling energy and agriculture interactions—I: A rural energy systems model

Since many of the factors related to rural energy systems are gradually being quantified, there is a need to construct a model that integrates a number of these factors simultaneously in a consistent framework. Therefore, a general linear programming model is developed to capture energy and agricultural interactions existing in the rural areas of developing countries. Energy used for agriculture includes fertilizers, irrigation, and mechanization. Several technological choices of each of the above are considered and so are several crop commodities, several types of livestock, and farmers of different income groups along with their assets, i.e. land holdings, livestock, etc. The by-products of agriculture, i.e. biomass, such as crop residues, animal dung, wood, etc., can be used to generate energy. On the demand side the use of them for feed, fuel, and fertilizer must be considered. Thus, the household sector (which is the largest user of noncommercial energy), as well as the rural industries sector, is intimately related to the agriculture sector. Twelve different energy sources and several conversion technologies, such as biogas, charcoal kilns, alcohol distilleries, etc., are considered. The model is applicable to low-income, biomass-scarce developing countries. However, different types of countries will require different approximations, and their needs for detailing some aspects or other may vary. The model is suitable for policy purposes because it considers several income groups separately and considers how different changes affect each of them.     

AlGaN/GaN HEMTs-an overview of device operation and applications

Wide bandgap semiconductors are extremely attractive for the gamut of power electronics applications from power conditioning to microwave transmitters for communications and radar. Of the various materials and device technologies, the AlGaN/GaN high-electron mobility transistor seems the most promising. This paper attempts to present the status of the technology and the market with a view of highlighting both the progress and the remaining problems.     

Synthesis and characterization of butyl acrylate graft sodium salt of partially carboxymethylated starch

Graft copolymers were synthesized by graft copolymerization of butyl acrylate (BA) onto sodium salt of partially carboxymethylated starch (Na‐PCMS). Ceric ammonium nitrate (CAN), a redox initiator, was used for initiation of graft copolymerization reaction. All the experiments were run with Na‐PCMS having degree of substitution, DS = 0.35. The grafting reaction was characterized by parameters such as % total conversion (%Ct), % grafting (%G), % grafting efficiency (%GE), and % add‐on. Graft copolymers were characterized by infrared spectral analysis and scanning electron microscopy. Variables affecting graft copolymerization reaction such as nitric acid concentration, reaction time, reaction temperature, and ceric ion concentration were investigated. The results revealed that 0.3M CAN as initiator, 0.3M HNO₃, with reaction time 4–4.5 h at 25–30°C were found as suitable parameters for maximum yield of graft copolymerization reaction. © 2006 Wiley Periodicals, Inc. JAppl Polym Sci 102: 3334–3340, 2006     

Impact of hydrogen generated by splitting water with nano-silicon and nano-aluminum on diesel engine performance

Efficient utilization of hydrogen generated during the reactions of nano-silicon/water and nano-aluminum/water in internal combustion engine has been investigated in the current work. Engine performance and emission studies of formulated and stabilized nanoemulsion fuels (water in diesel W/D), nano-aluminum in water/diesel (W/DA) and water in nano-silicon/diesel (W/DS) have been compared with those of diesel. Experimental investigations showed reduction in brake specific fuel consumption (BSFC) by 21% and 37%; rise in brake thermal efficiency (BTE) by 16% and 14% when engine was fueled with W/DA and W/DS respectively. For nanoemulsion fuels an increase in induced power was also recorded. Brake mean effective pressure, BTE and NOx emission dropped for W/D due to reduced exhaust gas temperatures. Nevertheless due to elevated peak cylinder pressures and exhaust gas temperatures a marginal rise in NOx, CO, HC and radiative heat emissions was observed with W/DA and W/DS.     

A Brief Review on the Biology and Effects of Cellular and Circulating microRNAs on Cardiac Remodeling after Infarction

Despite advances in diagnostic, prognostic, and treatment modalities, myocardial infarction (MI) remains a leading cause of morbidity and mortality. Impaired cellular signaling after an MI causes maladaptive changes resulting in cardiac remodeling. MicroRNAs (miRNAs/miR) along with other molecular components have been investigated for their involvement in cellular signaling in the pathogenesis of various cardiac conditions like MI. miRNAs are small non-coding RNAs that negatively regulate gene expression. They bind to complementary mRNAs and regulate the rate of protein synthesis by altering the stability of their targeted mRNAs. A single miRNA can modulate several cellular signaling pathways by targeting hundreds of mRNAs. This review focuses on the biogenesis and beneficial effects of cellular and circulating (exosomal) miRNAs on cardiac remodeling after an MI. Particularly, miR-1, -133, 135, and -29 that play an essential role in cardiac remodeling after an MI are described in detail. The limitations that will need to be addressed in the future for the further development of miRNA-based therapeutics for cardiovascular conditions will also be discussed.     

DEVOLATILIZATION STUDIES ON A BITUMINOUS COAL UNDER VARIOUS GAS ENVIRONMENTS

ABSTRACT

Devolatilization of a bituminous coal was studied in the temperature range 3 50°C to 550°C and at two pressures: 30 psig and 375 psig. Three separate particle sizes were investigated: (?2, +l),(?4, +3) and (?9, +6) mm. The runs, lasting up to 30 minutes, were carried out under two different types of flowing gas environments: a synthetic gas mixture of composition similar to that entering the devolatilization zone from the gasification zone below in a fixed bed gasifier, and containing 3% steam by volume; and, a helium-steam mixture, also containing 3% steam by volume.

The gas evolution rates from devolatilization show a peak at 5–10 minutes from the start of a run and then gradually taper off to zero as the run progresses. The concentration of methane in the off-gas stream is observed to be higher in the helium runs. There, however, is no significant effect of gas environment on the molecular weights of the tar, which show a maximum in the range 300–500. The tar yields, however, are higher for the helium runs; in all cases, the tar yields peak at 4 °C. The gas yield, however, is higher for the reactive gas environment. The total volatiles yield appears independent of particle size; however, it seems to increase with pressure, over the temperature range studied.     

Cloud classification from visible and infrared SMS-1 data

The success of a statistical classification-design sample model in discriminating cloud-type samples of visible and infrared meteorological satellite data depends on the selection of the design parameters for the system and the ability of the labelled design samples to characterize and discriminate class patterns within the given geographical region. In a companion study by Parikh (1977), pattern recognition design parameters were examined for a four-class problem and a three-class problem for NOAA-1 cloud data. The purpose of this study was to evaluate pattern recognition systems designed in the previous study on SMS-1 design and test sets. Experiments were conducted for both a four-class problem (separation of “low”, “mix”, “cirrus”, and “cumulonimbus” samples) and a three-class problem (separation of “low”, “cirrus”, and “cumulonimbus” samples). For the four-class problem, decreases in classification accuracy ranging from 4% to 11% occurred when the pattern recognition systems were designed and tested on two different data sets selected from the same satellite orbit. A similar decrease was not observed for the well-defined three-class problem.     

Boundary layer scattering measurements with a charge-coupled device camera lidar

A CCD-based bistatic lidar (CLidar) system has been developed and constructed to measure scattering in the atmospheric boundary layer. The system uses a CCD camera, wide-angle optics, and a laser. Imaging a vertical laser beam from the side allows high-altitude resolution in the boundary layer all the way to the ground. The dynamic range needed for the molecular signal is several orders of magnitude in the standard monostatic method, but only approximately 1 order of magnitude with the CLidar method. Other advantages of the Clidar method include low cost and simplicity. Observations at Mauna Loa Observatory, Hawaii, show excellent agreement with the modeled molecular-scattering signal. The scattering depends on angle (altitude) and the polarization plane of the laser.     

An ensemble-based incremental learning approach to data fusion.

This paper introduces Learn++, an ensemble of classifiers based algorithm originally developed for incremental learning, and now adapted for information/data fusion applications. Recognizing the conceptual similarity between incremental learning and data fusion, Learn++ follows an alternative approach to data fusion, i.e., sequentially generating an ensemble of classifiers that specifically seek the most discriminating information from each data set. It was observed that Learn++ based data fusion consistently outperforms a similarly configured ensemble classifier trained on any of the individual data sources across several applications. Furthermore, even if the classifiers trained on individual data sources are fine tuned for the given problem, Learn++ can still achieve a statistically significant improvement by combining them, if the additional data sets carry complementary information. The algorithm can also identify-albeit indirectly-those data sets that do not carry such additional information. Finally, it was shown that the algorithm can consecutively learn both the supplementary novel information coming from additional data of the same source, and the complementary information coming from new data sources without requiring access to any of the previously seen data.