Comparative time series RNA-seq analysis of Pigeonpea Root Tissues in response to Fusarium udum infection

Pigeonpea [Cajanus cajan (L.) Millsp.] is an important food legume and is mostly cultivated in tropical and subtropical regions of South Asia, Kenya, Malawi, Bangladesh, and other parts of the world. India is the center of origin and major global producer (66%), consumer, and importer, ahead of production in Africa (14%)..

A novel economical grain boundary engineered ultra-high performance ZnO varistor with lesser dopants

A varistor having ultra-high performance was developed from doped ZnO nanopowders using a novel composition consisting of only three (Bi, Ca and Co oxides) dopants. Improved varistor properties were obtained (breakdown field (E-b) 27.5 +/- 5 kV cm(-1), coefficient of nonlinearity (alpha) 72 +/- 3 and leakage current density (Lc) 1.5 +/- 0.06 mu Acm(-2)) which are attributed to the small grain size and grain boundary engineering by phases such as Ca4Bi6O13 and Ca0.89Bi3.11O5.56 along with Co+2 doping in the ZnO lattice. Complex impedance data indicated three relaxations at 25 degrees C and two relaxations at high temperature (>100 degrees C). The complex impedance data were fitted into two parallel RC model to extract electrical properties. Two stages of activation energy for DC conductivity were observed in these varistor samples where region I (< 150 degrees C) is found to be due to shallow traps and region II (< 225 degrees C) is due to deep traps. The novel composition is useful for commercial exploitation in wide range of surge protection applications

Prevalence of gastrointestinal helminths in Banaraja fowls reared in semi-intensive system of management in Mayurbhanj district of Odisha

Aim: Studies on the prevalence of gastrointestinal helminths infection in Banaraja fowls of Mayurbhanj district in Odisha with respect to semi-intensive system of rearing. Materials and Methods: A total of 160 Banaraja birds (30 males and 130 females) belonging to two age groups (below 1 month age and above 1 month) were examined for the presence of different species of gastrointestinal helminth infection over a period of 1-year. The method of investigation included collection of fecal sample and gastrointestinal tracts, examination of fecal sample of birds, collection of parasites from different part of gastrointestinal tract, counting of parasites, and examination of the collected parasites by standard parasitological techniques followed by morphological identification as far as possible up to the species level. Results: Overall, 58.75% birds were found infected with various gastrointestinal helminths. Total five species of parasites were detected that included Ascaridia galli (25.63%), Heterakis gallinarum (33.75%), Raillietina tetragona (46.25%), Raillietina echinobothrida (11.87%), and Echinostoma revolutum (1.87%). Both single (19.15%) as well as mixed (80.85%) infection were observed. Highest incidence of infection was observed during rainy season (68.88%) followed by winter (66.66%) and least in summer season (41.81%). Sex-wise incidence revealed slightly higher occurrence among females (59.23%) than males (56.67%). Age-wise prevalence revealed that chicks were more susceptible (77.77%) than adults (51.30%) to gastrointestinal helminths infection. Conclusions: Present study revealed that mixed infection with gastrointestinal helminths of different species was more common than infection with single species and season-wise prevalence was higher in rainy season followed by winter and summer. Chicks were found to be more prone to this parasitic infection and a slight higher prevalence among female birds was observed

Comparison between Deep Learning and Tree-Based Machine Learning Approaches for Landslide Susceptibility Mapping

The efficiency of deep learning and tree-based machine learning approaches has gained immense popularity in various fields. One deep learning model viz. convolution neural network (CNN), artificial neural network (ANN) and four tree-based machine learning models, namely, alternative decision tree (ADTree), classification and regression tree (CART), functional tree and logistic model tree (LMT), were used for landslide susceptibility mapping in the East Sikkim Himalaya region of India, and the results were compared. Landslide areas were delimited and mapped as landslide inventory (LIM) after gathering information from historical records and periodic field investigations. In LIM, 91 landslides were plotted and classified into training (64 landslides) and testing (27 landslides) subsets randomly to train and validate the models. A total of 21 landslides conditioning factors (LCFs) were considered as model inputs, and the results of each model were categorised under five susceptibility classes. The receiver operating characteristics curve and 21 statistical measures were used to evaluate and prioritise the models. The CNN deep learning model achieved the priority rank 1 with area under the curve of 0.918 and 0.933 by using the training and testing data, quantifying 23.02% and 14.40% area as very high and highly susceptible followed by ANN, ADtree, CART, FTree and LMT models. This research might be useful in landslide studies, especially in locations with comparable geophysical and climatological characteristics, to aid in decision making for land use planning

Ignition delay studies on hydrocarbon fuel with and without additives

Single pulse shock tube facility has been developed in the High Temperature Chemical Kinetics Lab, Aerospace Engineering Department, to carry out ignition delay studies and spectroscopic investigations of hydrocarbon fuels. Our main emphasis is on measuring ignition delay through pressure rise and by monitoring CH emission for various jet fuels and finding suitable additives for reducing the delay. Initially the shock tube was tested and calibrated by measuring the ignition delay of C2H6-O2 mixture. The results are in good agreement with earlier published works. Ignition times of exo-tetrahdyrodicyclopentadiene (C10H16), which is a leading candidate fuel for scramjet propulsion has been studied in the reflected shock region in the temperature range 1250 - 1750 K with and without adding Triethylamine (TEA). Addition of TEA results in substantial reduction of ignition delay of C10H16

Synthesis, structure, and properties of mesoporous B/C/N microspheres

Reaction of low surface area carbon with a mixture of urea and boric acid at 930&#176;C yields a composition close to BC<SUB>4</SUB>N with a graphitic structure. BC<SUB>4</SUB>N was characterized by electron energy loss spectroscopy, X-ray photoelectron spectroscopy, transmission electron microscopy, Raman spectroscopy, and X-ray diffraction. BC<SUB>4</SUB>N is a porous ceramic with a surface area of 428 m<SUP>2</SUP>&#183;g<SUP>&#8722;1</SUP>, and shows a CO<SUB>2</SUB> uptake of 40 wt-%. The layered structure of BC<SUB>4</SUB>N involves a random distribution of boron, carbon, and nitrogen atoms and shows high thermal stability up to 1000&#176;C. A comparative analysis of the structure and properties of BC<SUB>4</SUB>N and graphene using first-principles pseudopotential based density functional theoretical calculations is presented. The calculations predict it to be an insulator. The bulk modulus of BC<SUB>4</SUB>N exhibits an interesting dependence on the ordering of boron and nitrogen on the graphene lattice