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Joshi, Vandana
- Guayule (parthenium argentatium) : a Lesser Known Potential Source of Natural Rubber
Authors
Source
Indian Forester, Vol 120, No 6 (1994), Pagination: 519-523Abstract
Guayule (Parthenium argentatium) is capable of producing commercial rubber in wastelands and marginal areas of the country. This paper describes adaptation, botany, geneties and breeding behaviour, rubber extraction methodology, agroclimatic requirements and cultivation practices of Guayule. The research work done under the All Indla Coordinated Research Project on under utilised plants as well as research needs and future prospects of commercialisation of this plant have been mentioned.- Evaluation of Antimicrobial Potency and Synergistic Activity of Nine Traditionally Used Indian Medicinal Plants
Authors
1 M. C. E. Society’s Allana College of Pharmacy, Azam Campus, Camp, Pune, 411001, Maharashtra, IN
2 M.C.E. Society’s Allana College of Pharmacy, Pune, IN
3 Abeda Inamdar Senior College for Girls, Pune, IN
Source
Research Journal of Pharmacognosy and Phytochemistry, Vol 2, No 2 (2010), Pagination: 131-135Abstract
Recent acceptance of natural herbal medicines as an alternative form of health care and development of microbial resistance has led to investigate the antimicrobial action of medicinal plants. Present investigation is focused on antimicrobial potential of nine commonly used Indian medicinal herbs. The antimicrobial screening of hydroalcoholic extract of all the nine plants was carried out by agar welldiffusion method and broth dilution method. The efficacy of extracts has been evaluated in terms of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) against pathogenic strains of Staphylococcus aureus (ATCC 6538), Pseudomonas aeruginosa (ATCC 9027) and Candida albicance (ATCC 10231). MIC values of individual extracts ranged between 0.4-0.9 mg/ml. MIC values of the combined crude extracts were recorded as 0.3 mg/ml (C. albicance ) , 0.5 mg/ml (Staph. aureus), and 0.6 mg/ml (P. aeruginosa) . The MIC values obtained in each test organisms were inhibitory as well as cidal values. Susceptibility of test organisms was in decreasing order C. albicance > Staph . aureus > P. aeruginosa. Thus our findings validate the use of these medicinal plants in traditional systems of medicines and their potential role in antimicrobial therapy.
Keywords
Antimicrobial Activity, Hydro Alcoholic Extract, Synergistic Activity.- Self-Help Groups in Empowering Women:A Study in Udaipur and Jhalawar Districts of Rajasthan
Authors
1 AICRP – HECM, College of Home Science, Maharana Pratap University of Agriculture and Technology, Udaipur (Rajasthan), IN
2 College of Home Science, MaharanaPratap University of Agriculture and Technology, Udaipur (Rajasthan), IN
3 Department of Soil Science, Rajasthan College of Agriculture, Maharana Pratap University of Agriculture and Technology, Udaipur (Rajasthan), IN
Source
International Journal of Home Science Extension and Communication Management, Vol 4, No 1 (2017), Pagination: 57-60Abstract
The study was conducted in Udaipur and Jhalawar district of Rajasthan, to know the Empowerment status of SHG members. Total 1123 groups were registered during year 2008-09 by different forming agencies. In which, 102 SHGs were selected from NABARD, ICDS, DRDA and SAUs.Major finding revels that comparison of empowerment data before joining the SHGs, there was slight change in status of women, as before joining the SHG there were 33 office bearers who were found in the low empowerment category of legal and political empowerment however, after becoming the member of SHGs the percentage decreased upto 10 per cent and only 24 office bearers remained in this category.Keywords
Self-Help Groups, Empowerment, Empowering Women.References
- Antwal, P.N., Bellurkar, C.M. and Rathod, S.M. (2015). Dynamics and performance of women self help groups from Hingoli district. Internat. J. Appl. Soc. Sci., 2 (3&4) : 69-77.
- Archana and Singh, B.B. (2002). Performance of self help groups in economic empowerment of rural women. Indian Res. J. Extn. Edu., 2(1):13-17.
- Bairwa, Shoji Lal, Kushwaha, Saket, Lakra, Kerobim and Meena, Lokesh Kumar (2014). Women empowerment through agri-clinics and agri-business centres scheme in India. Internat. J. Com. & Bus. Manage, 7(1) : 181-185.
- Chopde, K.D., Kadam, M.M. and Bondhare, V.O. (2015).Role of self help groups in rural credit for women empowerment. Internat. Res. J. Agric. Eco. & Stat., 6 (1) : 160-163.
- Gupta, Nidhi and Patel, Komal (2015).Women empowerment through Mahatma Gandhi National Rural Employment in Anand district. Internat. J. Appl. Home Sci., 2 (1&2) : 60-64.
- Jobpaul, K.D.L. and Muthyalu, J. (2012). Women empowerment through SHG’s. Internat. J. Com. & Bus. Manage, 5(1): 98 - 104.
- Kappa, Kondal (2014). Women empowerment through self help groups in Andhra Pradesh, India. Internat. Res. J. Soc. Sci., 3 (1) : 13-17.
- Kaur, Kanwaljit, Mann, Sukhdeep Kaur and Kaur, Prabhjot (2011). Strategies for women empowerment. Adv. Res. J. Soc. Sci., 2 (2) : 275-278.
- Vinayamoorthy, A. and Pithoda, Vijay (2007). Women empowerment through SHG: A case study in North Tamil Nadu. Indian J. Mktg., 37 (11) : 32-35.
- Census (2011). Retrived from tribal.nic.in. onfebruary 10, 2016.
- Fake News Detection Using Hybrid Approach
Authors
1 Department of Computer Engineering, Sarvajanik College of Engineering and Technology, Athwalines, Athwa, Surat - 395001, Gujarat, IN
Source
Journal of Information and Knowledge (Formerly SRELS Journal of Information Management), Vol 61, No 2 (2024), Pagination: 77-82Abstract
Over the last few years, fake news has dramatically increased on social media. Fake news can originate from any number of sources and is shared across different social platforms. This type of information is used to spread for fun or economic gain. Our goal is to stop distributing this type of misleading information on social media or any other platform. In this paper, we have proposed a hybrid model (RoBERTa and BERT) to detect fake news. Our proposed architecture is based on the LIAR multi-label dataset. Our model shows promising results.Keywords
BERT, Fake News, RoBERTa, Social MediaReferences
- Devlin, J., Chang, M.-W., Lee, K., Google, K. T., & Language, A. I. BERT: Pre-training of deep bidirectional transformers for language understanding. https://github.com/tensorflow/ tensor2tensor
- Goldani, M. H., Momtazi, S., & Safabakhsh, R. (2021). Detecting fake news with capsule neural networks. Applied Soft Computing, 101, 106991. https://doi.org/10.1016/j. asoc.2020.106991
- Jadhav, S. S., & Thepade, S. D. (2019). Fake news identification and classification using DSSM and improved recurrent neural network classifier. Applied Artificial Intelligence, 1–11. https://doi.org/10.1080/08839514.2019.1661579
- Li, Y., Jiang, B., Shu, K., & Liu, H. (2020). Toward a multilingual and multimodal data repository for COVID- 19 disinformation. International Conference on Big Data. https://doi.org/10.1109/bigdata50022.2020.9378472
- Liu, J., Wang, C., Li, C., Li, N., Deng, J., & Pan, J. Z. (2021). DTN: Deep triple network for topic specific fake news detection. Journal of Web Semantics, 100646. https://doi. org/10.1016/j.websem.2021.100646
- Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M. S., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019). RoBERTa: A robustly optimized BERT pretraining approach. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.1907.11692
- Nagoudi, E. B., Elmadany, A. R., Abdul-Mageed, M., Alhindi, T., & Cavusoglu, H. Machine generation and detection of Arabic manipulated and fake news. (2020). Proceedings of the Fourth Arabic Natural Language Processing Workshop, Barcelona, Spain.
- Nasir, J. A., Khan, O. S., & Varlamis, I. (2021). Fake news detection: A hybrid CNN-RNN based deep learning approach. International Journal of Information Management Data Insights, 1(1), 100007. https://doi.org/10.1016/j. jjimei.2020.100007
- Paka, W. S., Bansal, R., Kaushik, A., Sengupta, S., & Chakraborty, T. (2021). Cross-SEAN: A cross-stitch semisupervised neural attention model for COVID-19 fake news detection. Applied Soft Computing, 107, 107393. https://doi.org/10.1016/j.asoc.2021.107393 PMid:36568256 PMCid:PMC9761197
- Probierz, B., Stefański, P., & Kozak, J. (2021). Rapid detection of fake news based on machine learning methods. Procedia Computer Science, 192, 2893–2902. https://doi. org/10.1016/j.procs.2021.09.060
- Shim, J.-S., Lee, Y., & Ahn, H. (2021). A link2vec-based fake news detection model using web search results. Expert Systems with Applications, 184, 115491. https://doi. org/10.1016/j.eswa.2021.115491
- Wang, W. Y. (n.d.). Liar, liar pants on fire: A new benchmark dataset for fake news detection. https://www.cs.ucsb.edu/