Implication of scanning electron microscopy as a tool for identification of novel,nonedible oil seeds for biodiesel production

Biodiesel is a promising, bio-based, renewable, nontoxic, environment friendly, and alternative fuel for petroleum derived fuels which helps to reduce dependency on conventional fossil fuels. In this study, six novel, nonedible seed oil producing feedstock were explored for their potential for sustainable production of biodiesel. It is very important to correctly identify oil yielding plant species. Scanning electron microscopy (SEM) was used as reliable tool for authentic identification of oil yielding seeds. Macromorphological characters of seeds were studied with light microscopy (LM). Outcomes of LM of seeds exposed distinctive variation in seed size from 16.3 to 3.2 mm in length and 12.4 to 0.9 mm in width, shape varied from oval to triangular, and color from black to light brown. Oil content of nonedible seed ranged from 25 to 30% (w/w). Free fatty acid content of seed oil varied from 0.32 to 2.5 mg KOH/g. Moreover, ultra structural study of seeds via SEM showed variation in surface sculpturing, cell arrangement, cell shape, periclinal wall shape, margins, protuberances, and anticlinal wall shape. Surface sculpturing varied from rugged, reticulate, varrucose, papillate, and striate. Periclinal wall arrangements confirmed variation from rough, wavy, raised, depressed, smooth, and elevated whereas, anticlinal walls pattern showed variation from profuse undulating, smooth, raised, grooved, deep, curved, and depressed. It was concluded that SEM could be a latent and advanced technique in unveiling hidden micromorphological characters of nonedible oil yielding seeds which delivers valuable information to researchers and indigenous people for precise and authentic identification and recognition.     

Patterns of empowerment and leadership style in project environment

The current study explores the relationship of empowerment, leadership style and customer service as a measure of effective project management in projects with varying degree of virtuality. The study makes comparisons of empowerment climate in less and more virtual projects. Moreover, the study examines moderating effects of degree of virtuality on the relationship between empowerment and leadership style. We test our hypotheses with data collected from project management professionals working in five countries using linear regression and moderated regression analysis to analyze the proposed hypotheses.     

Automatic Fish Species Classification Using Deep Convolutional Neural Networks

A piezoelectric sensor based energy efficient transmission using base station controlled dynamic clustering protocol (BSCDCP) is proposed in this work. The piezoelectric sensor design and simulation is analyzed with the help of COMSOL finite element modeling and location based energy efficient routing is estimated by BSCDCP hierarchical routing techniques. The sensor voltage 5.2 V^–1 g acceleration and electrical load impedance 12 Ω is distributed uniform voltage to all the nodes and analyze piezoelectric sensor performance based on BSCDCP protocol. The number of iterations the life time of sensor node is increasing with the help of piezoelectric sensor. The numerical results show that 95% accuracy when increase the distance and number of nodes also it suggest to improve the life time of piezoelectric sensor. By using BSCDCP protocol, the optimize piezoelectric sensor frequency and generated voltage is enhance and time duration 0.5 µs is achieved and simulation done with number of nodes, which is very fast compared to existing protocol techniques. The overall protocol is best suitable for energy efficient routing for large volume with less latency and accuracy.

     

Instance optimal query processing in spatial networks

The performance optimization of query processing in spatial networks focuses on minimizing network data accesses and the cost of network distance calculations. This paper proposes algorithms for network k-NN queries, range queries, closest-pair queries and multi-source skyline queries based on a novel processing framework, namely, incremental lower bound constraint. By giving high processing priority to the query associated data points and utilizing the incremental nature of the lower bound, the performance of our algorithms is better optimized in contrast to the corresponding algorithms based on known framework incremental Euclidean restriction and incremental network expansion. More importantly, the proposed algorithms are proven to be instance optimal among classes of algorithms. Through experiments on real road network datasets, the superiority of the proposed algorithms is demonstrated.     

A web-based approach to data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques.     

Green and eco-friendly synthesis of cobalt-oxide nanoparticle: Characterization and photo-catalytic activity

Cobalt-oxide nanoparticles (NPs) were fabricated using Punica granatum peel extract from cobalt nitrate hexahydrate at low temperature. The synthesized cobalt-oxide NPs were characterized using X-ray powder diffraction, scanning electron microscopy, energy-dispersive X-ray, atomic force microscopy, fourier transform infrared spectroscopy and UV-visible techniques. The cobalt-oxide NPs were in highly uniform shape and size was in the size of 40–80 nm. Photo-catalytic activity (PCA) of the synthesized NPs was evaluated by degrading Remazol Brilliant Orange 3R (RBO 3R) dye and a degradation of 78.45% was achieved (dye conc. 150 mg/L) using 0.5 g cobalt-oxide NPs for 50 min irradiation time. In view of eco-benign and cost-effective nature, the present investigation revealed that P. granatum could be used for the synthesis of cobalt-oxide NPs for photo-catalytic applications.     

Identification of monocot flora using pollen features through scanning electron microscopy

Pollen used to track structural and functional evolution in plants as well as to investigate the problems relative to plant classification. Pollen characters including ornamentation, shape, apertural pattern, pollen symmetry, colpus length, width, and margins used to detect the similarities and dissimilarities between genera and also species of the same genus. In this study pollen features of 20 monocot species belonging to 15 genera of the Amaryllidaceae, Asparagaceae, Iridaceae, Ixioliriaceae, Liliaceae, and Xanthorrhoeaceae were studied using scanning electron microscopy (SEM) and light microscopy (LM). In this study two species that is Zephyranthes citrina and Tulbaghia violacea were reported for the first time from Pakistan. Pollen grains were visualized with LM. Non‐acetolyzed and acetolyzed pollen were examined using SEM. A taxonomic key was developed to highlight the variation in pollen features in order to make their systematic application for correct species identification.