Improvement of fuel properties of cottonseed oil methyl esters with commercial additives

The low temperature operability and oxidative stability of cottonseed oil methyl esters (CSME) were improved with four anti‐gel additives as well as one antioxidant additive, gossypol. Low temperature operability and oxidative stability of CSME was determined by cloud point (CP), pour point (PP), cold filter plugging point (CFPP), and oxidative stability index (OSI). The most significant reductions in CP, PP, and CFPP in all cases were obtained with Technol®, with the average reduction in temperature found to be 3.9 °C. Gunk®, Heet®, and Howe's® were progressively less effective, as indicated by average reductions in temperature of 3.4, 3.0, and 2.8 °C, respectively. In all cases, the magnitude of CFPP reduction was greater than for PP and especially CP. Addition of gossypol, a polyphenolic aldehyde, resulted in linear improvement in OSI (R² = 0.9804). The OSI of CSME increased from 5.0 to 8.3 h with gossypol at a concentration of 1000 ppm.     

Effect of Ar heat treatment on oxygenated R1−x Ca x Ba2Cu3O7−δ (R = Y, Sm) superconductors

The influence of heat treatment, at 450°C in Ar environment, on oxygenated (6.72 < 7 – < 6.93) samples of R_1–x Ca _x Ba₂Cu₃O_7– (i.e. R(Ca)-123, with R = Y, Sm) with 0 < x < 0.3 has been investigated. Measurements of oxygen loss, normal state resistivity behaviour (T), superconducting critical temperature T _c and transition widths reveal that Ar treatment effects both the series differently. The Sm(Ca)-123 samples, for all values of x, show a considerable loss of oxygen ((x) = 0.4 to 0.6) and decrease in T _c (T _c(x) = 35 to 55 K). Whereas, surprisingly, the Y(Ca)-123 samples show a much smaller loss of oxygen ((x) = 0 to 0.3), along with a decrease in T _c for x < 0.2 and an increase in it for x > 0.2. In particular, the x = 0.3 sample shows a negligible change in oxygen content accompanied by an increase of 20 K in T _c. These and host of other observations suggest that the presence of Ca may influence the oxygen loss mechanism in these series.     

Application of Fuzzy Logic to Estimate Flow of Methane for Energy Generation at a Sanitary Landfill

This paper proposes the use of a multicriteria assessment technique to evaluate the methane flow during gas extraction from a sanitary landfill. A number of parameters determine the gas generation and the feasibility for its extraction from a landfill. These parameters form a complex set of information with unknown mathematical interrelationships making potential gas flow evaluations difficult and elusive. In addition, the data available for a particular landfill are very often imprecise, uncertain, or subjective, making it even more difficult to evaluate the potential for gas extraction without conducting pilot tests. The method proposed in this paper uses fuzzy composite programming that allows for the use of imprecise information. A landfill gas potential index has been defined, which can be determined by easily obtainable climatological, geological, and landfill parameters. The landfill gas (LFG) potential index is related to the landfill gas flow using an empirical equation. The LFG potential model was calibrated and verified using data obtained from 61 landfills where gas extraction is being conducted. A sensitivity analysis was done to study the impact of variations in the input data on model output.     

A Genetically-Based Latitudinal Cline in the Emission of Herbivore-Induced Plant Volatile Organic Compounds

The existence of predictable latitudinal variation in plant defense against herbivores remains controversial. A prevailing view holds that higher levels of plant defense evolve at low latitudes compared to high latitudes as an adaptive plant response to higher herbivore pressure on low-latitude plants. To date, this prediction has not been examined with respect to volatile organic compounds (VOCs) that many plants emit, often thus attracting the natural enemies of herbivores. Here, we compared genetically-based constitutive and herbivore-induced aboveground vegetative VOC emissions from plants originating across a gradient of more than 10° of latitude (>1,500 km). We collected headspace VOCs from Asclepias syriaca (common milkweed) originating from 20 populations across its natural range and grown in a common garden near the range center. Feeding by specialist Danaus plexippus (monarch) larvae induced VOCs, and field environmental conditions (temperature, light, and humidity) also influenced emissions. Monarch damage increased plant VOC concentrations and altered VOC blends. We found that genetically-based induced VOC emissions varied with the latitude of plant population origin, although the pattern followed the reverse of that predicted—induced VOC concentration increased with increasing latitude. This pattern appeared to be driven by a greater induction of sesquiterpenoids at higher latitudes. In contrast, constitutive VOC emission did not vary systematically with latitude, and the induction of green leafy volatiles declined with latitude. Our results do not support the prevailing view that plant defense is greater at lower than at higher latitudes. That the pattern holds only for herbivore-induced VOC emission, and not constitutive emission, suggests that latitudinal variation in VOCs is not a simple adaptive response to climatic factors.     

Supporting ordinal four-state classification decisions using neural networks

Many accounting and finance problems require ordinal multi-state classification decisions, (e.g., control risk, bond rating, financial distress, etc.), yet few decision support systems are available to aid decision makers in such tasks. In this study, we develop a Neural Network based decision support system (NN-DSS) to classify firms in four ordinal states of financial condition namely healthy, dividend reduction, debt default and bankrupt. The classification results of the NN-DSS model are compared with those of a Naïve model, a Multiple Discriminant Analysis (MDA) model, and an Ordinal Logistic Regression (OLGR) model. Four different evaluation criteria are used to compare the models, namely, simple classification accuracy, distance-weighted classification accuracy, expected cost of misclassification (ECM) and ranked probability score. Our study shows that NN-DSS models perform significantly better than the Naïve, MDA, and OLGR models on the ECM criteria, and provide better results than MDA and OLGR on other criteria, although not always significantly better. The effect of the proportion of firms of each state in the training set is also studied. A balanced training set leads to more uniform (less skewed) classification across all four states, whereas an unbalanced training set biases the classification results in favor of the state with the largest number of observations.     

Effect of accelerated aging on the tensile index of a synthetic insulation paper

This paper explores the possibility of using tensile index as one of the appropriate end point parameters to determine the thermal index of a synthetic insulation paper. The paper samples were aged at three different times and temperatures. The tensile index of fresh as well as aged samples was determined experimentally. The study showed that tensile index could be considered as an appropriate parameter to find the thermal index of the chosen synthetic insulation paper.     

Contamination of surface and potable water in South Asia by Salmonellae: Culture-independent quantification with molecular beacon real-time PCR

Low numbers (15-100 CFU) of Salmonella in food or water may pose a public health risk. The management of infections caused by Salmonella spp. during outbreaks or forecasting of contamination of aquatic resources largely depends on rapid, sensitive and accurate diagnostic in few hours. In this study, a real-time PCR assay in Molecular-Beacon format was developed and culture-independent quantitative enumeration of Salmonella spp. in surface and potable water is being reported for the first time from northern part of India. Molecular Beacon was designed in highly conserved region of invA gene (present in wide range of Salmonella serotypes including all subspecies) encoding an essential component of the invasion associated specialized type Ø protein secretion apparatus for detection of Salmonella spp. in water. The assay could detect directly 10 and 1 genomic equivalent of Salmonella typhimurium ATCC 14028 per PCR with detection probability of 100 and 20%, respectively. Further, the assay could detect 10 CFU/PCR or more of reference strain (S. typhimurium ATCC 14028) without any enrichment in the presence of 10⁸ CFU ml^− 1 of non-pathogenic E. coli (E. coli DH5α) with 100% detection probability. The assay could enumerate Salmonella spp. in surface (n = 40) and potable waters (n = 10) directly (without enrichment). Results indicate that northern India is at high risk of developing Salmonella borne infections. Further, real-time PCR assay in Molecular Beacon format can be used for identification of critical contamination points in natural water resources and potable water distribution systems, necessary to implement vaccination plan timely for prevention of waterborne outbreaks caused by Salmonella spp.