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The cloud computing platform has become prevalent today and is being utilized by many organizations in government, industry, and academia. For teaching and training, its virtual environment provides a cost-effective alternative to physical labs which may be rapidly configured to provide hands-on lab exercises, as well as to run scientific applications for e-learning. In this paper, we present a survey of cloud usage aimed at empowering students with practical skills in an educational environment. We present a taxonomy of cloud usage for e-learning, and also analyze existing major contributions relevant to cloud usage for e-learning. We also perform a comparative analysis of the frameworks and models found in the literature along with a comparative evaluation of the implementations carried out for e-learning. The future challenges and major issues being faced in adopting cloud technology for e-learning are also discussed along with recommendations for possible solutions.

The Extensible Markup Language (XML) files, widely used for storing and exchanging information on the web require efficient parsingmechanisms to improve the performance of the applications. With the existing Document Object Model (DOM) based parsing, the performance degrades due to sequential processing and large memory requirements, thereby requiring an efficient XML parser to mitigate these issues. In this paper, we propose a Parallel XML Tree Generator (PXTG) algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework (RXPF) that analyzes and predicts performance through profiling, regression, and code generation for efficient parsing. The PXTG algorithm is based on dividing the XML file into n parts and producing n trees in parallel. The profiling phase of the RXPF framework produces a dataset by measuring the performance of various parsing models including StAX, SAX, DOM, JDOM, and PXTG on different cores by using multiple file sizes. The regression phase produces the prediction model, based on which the final code for efficient parsing of XML files is produced through the code generation phase. The RXPF framework has shown a significant improvement in performance varying from 9.54% to 32.34% over other existing models used for parsing XML files. [ABSTRACT FROM AUTHOR]

Apitherapy (using bee products) has gained broad recognition in cancer therapeutics globally. Honeybee venom has a broad range of biological potential, and its utilization is rapidly emerging in apitherapy. Bee products have significant potential to strengthen the immune system and improve human health. Thus, this review is targeted toward recapitulating the chemo-preventive potential of melittin (MEL), which constitutes a substantial portion of honeybee venom. Honeybee venom (apitoxin) is produced in the venom gland of the honeybee abdomen, and adult bees utilize it as a primary colony defense mechanism. Apitoxin comprises numerous biologically active compounds, including peptides, enzymes, amines, amino acids, phospholipids, minerals, carbohydrates, and volatile components. We are mainly focused on exploring the potential of melittin (a peptide component) of bee venom that has shown promising potential in the treatment of several human cancers, including breast, stomach, lung, prostate, ovary, kidney, colon, gastric, esophageal, cervical cancers, melanoma, osteosarcoma, and hepatocellular carcinoma. This review has summarized all potential studies related to the anticancerous efficacy of melittin (apitoxin), its formulations, conjugates, and nano-formulations against several human carcinomas, which would further pave the way for future researchers in developing potent drugs for cancer management. [ABSTRACT FROM AUTHOR]

Economic losses arising from crop diseases caused by phytopathogenic fungi are principally associated with yield reductions. One alternative to fungicides is biocontrol with beneficial bacteria. Next to Pseudomonas, the endospore-forming genus Bacillus is probably the most widely researched and commercialized biocontrol agent. It is generally recognized that biological control agents are safer and more environmentally sound than is reliance on the use of high volumes of pesticides. The primary objective of current work was to isolate the specific bacterial strain that possesses the potential to act as an antagonist against the fungal pathogen Aspergillus which is thought to secrete aflatoxin, the most potent mycotoxin. Many bacterial cells were isolated randomly from the rhizospheric region of groundnut crop by serial dilution method, which were further screened for their antagonistic effect against Aspergillus. Screening results show that few of the isolates exhibit significant antagonism on dual culture media. One of the bacterial isolates SJ 609 exhibiting the maximum antagonistic effect was further selected after optimization for further studies. The mechanism of action of SJ 609 was studied in vitro for the production of hydrolytic enzymes particularly chitinase which hydrolyses chitin, which is the major component of fungal cell wall. Phylogenetic analysis using 16S rDNA amplification was carried out to establish its identity. [ABSTRACT FROM AUTHOR]

eXtensible Markup Language (XML) is gaining popularity and is being used widely on internet for storing and exchanging data. Large XML files when transferred on network create bottleneck and also degrade the query performance. Therefore, efficient mechanisms of compression and decompression are applied to XML files. In this paper, an algorithm for performing XML compression and decompression is suggested. The suggested approach reads an XML file, removes tags, divides the XML file into different parts and then compresses each different part on a separate core for achieving efficiency. We compare performance results of the proposed algorithm with parallel compression and decompression of XML files using GZIP. The performance results show that the suggested algorithm performs 24%, 53% and 72% better than the parallel GZIP compression and decompression on Intel Xeon, Intel core i7 and Intel core i3 based architectures respectively. [ABSTRACT FROM AUTHOR]

Contamination of major cash crops by mycotoxigenic fungi in developing countries, including India, is becoming one of the major areas of concern. Continual use of synthetic pesticides to fulfil the increasing demand for consumption of major legumes has negative impact on human health and has major environmental risks associated with it. Microbes living in vicinity to these mycotoxin producing fungi have been found to be a promising substitute against harmful pesticides. The main objective of the present work was to isolate the bacterial strain which has a promising potential to act as an antagonist against the fungal pathogen Aspergillus which is considered to secrete Aflatoxin, the most potent mycotoxin. Large number of bacteria were isolated randomly from the rhizosphere of groundnut crop sown in Jamia Hamdard (New Delhi, India) randomly by serial dilution method, and screened for their antagonistic effect against fungus Aspergillus. Initial screening results show that, 14 of the isolates exhibit promising antagonism on dual culture media. Optimization of growth conditions was carried out at different pH, temperature and salt (NaCl) concentration. In vitro antagonism assay comprising of mycelial inhibition assay on to PDA using the scale of 1-4 (where 1 indicates bacterial colony completely overgrown by fungi, 2 indicates overgrown but bacterial colony visible, 3 indicates growth of fungus to the edge of the bacterial colony and 4 indicates inhibition zone) and inhibition of mycelial growth as observed by a significant drop on mycelial dry weight by co-inoculation of bacterial culture with fungal spores in M1 media. One of the bacterial isolates MAK603 exhibiting the maximum antagonistic effect was selected after optimization for further studies. The mechanism of action of MAK603 was studied in vitro for the production of hydrolytic enzymes. Phylogenetic analysis using 16 S rDNA amplification was carried out to establish its identity. [ABSTRACT FROM AUTHOR]