Refine your search
Collections
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Watve, Milind
- Crop Damage by Wild Herbivores:Insights Obtained from Optimization Models
Abstract Views :247 |
PDF Views:71
Authors
Affiliations
1 Indian Institute of Science Education and Research, Homi Bhabha Road, Pashan, Pune 411 008, IN
2 Department of Ecology and Environmental Sciences, Pondicherry University, R.V. Nagar, Kalapet, Puducherry 605 014, IN
1 Indian Institute of Science Education and Research, Homi Bhabha Road, Pashan, Pune 411 008, IN
2 Department of Ecology and Environmental Sciences, Pondicherry University, R.V. Nagar, Kalapet, Puducherry 605 014, IN
Source
Current Science, Vol 111, No 5 (2016), Pagination: 861-867Abstract
We constructed a theoretical model of cost-benefit optimization for farmers who face continued economic loss due to crop raiding by wild herbivores, as well as for the wild herbivores that do so. Insights obtained from the model include: (i) In sustenance agriculture, a farmer needs to optimize net benefit rather than benefit-to-cost ratio, whereas herbivores need to optimize the benefit-to-cost ratio. (ii) It is imperative for a farmer to disinvest from agricultural inputs when threatened by depredation. (iii) Many mitigation measures that are highly successful on an experimental scale are most likely to fail when used on a mass scale. (iv) The effectiveness of mitigation measures such as fencing, trenching and culling will be non-monotonic, being counterproductive under certain conditions.Keywords
Agricultural Economics, Cost–Benefit Optimization, Crop Depredation, Optimal Foraging, Wildlife Management.- Polarity, Asymmetry and Aging:Are there Yayatis among Bacteria?
Abstract Views :263 |
PDF Views:74
Authors
Affiliations
1 Indian Institute of Science Education and Research, Dr Homi Bhabha Road, Pune 411 008, IN
1 Indian Institute of Science Education and Research, Dr Homi Bhabha Road, Pune 411 008, IN
Source
Current Science, Vol 113, No 04 (2017), Pagination: 553-554Abstract
Bacteria have been shown to age. In an exponentially growing population some cells progressively slow down and stop dividing. This is thought to be due to asymmetric damage segregation in which old pole cells retain damaged components and the new pole cells receive newly synthesized components. Polarity implies functional asymmetry with a predefined direction with or without morphological difference. Cellular polarity and division asymmetry are common to yeast, bacteria and stem cells of multi-cell organisms. A number of processes in bacteria, including formation of endospores, flagella, stalks or buds show clear polar biases.References
- Stewart, E. J., Madden, R., Paul, G. and Taddei, F., PLoS Biol., 2005, 3, 295–300.
- Ackermann, M., Stearns, S. C. and Jenal, U., Science, 2003, 300, 1920.
- Macara, I. G. and Mili, S., Cell, 2008, 135, 801–812.
- Cameron, T. A., Zupan, J. R. and Zambryski, P. C., Trends Microbiol., 2015, 23, 347–353.
- Lindner, A. B., Madden, R., Demarez, A., Stewart, E. J. and Taddei, F., Proc. Natl. Acad. Sci. USA, 2008, 105, 3076–3081.
- Baig, U. I., Bhadbhade, B. J., Mariyam, D. and Watve, M. G., PLoS One, 2014, 9, e107445.
- Chao, L., Rang, C. U., Proenca, A. M. and Chao, J. U., PLoS Comput Biol., 2016, 12, e1004700.
- Watve, M., Parab, S., Jogdand, P. and Keni, S., Proc. Natl. Acad. Sci. USA, 2006, 103, 14831–14835.
- Kysela, D. T., Brown, P. J. B., Huang, K. C. and Brun, Y. V., Annu. Rev. Microbiol., 2013, 67, 417–435.
- Vedel, S., Nunns, H., Košmrlj, A., Semsey, S. and Trusina, A., Cell Syst., 2016, 3, 187–198.
- Lele, U. N., Baig, U. I. and Watve, M. G., PLoS One, 2011, 6, e14516.
- Turke, P. W., Q. Rev. Biol., 2008, 83, 243–256.
- Baig, U., Sunny, R., Watve, M. and Lele, U., Matters, 2016, 2, e201603000022.
- Wang, P., Robert, L., Pelletier, J., Dang, W. L., Taddei, F., Wright, A. and Jun, S., Curr. Biol., 2010, 20, 1099–1103.
- Nakaoka, H. and Yuichi, W., BioRxiv., 2017, 1, 128298.
- Bergmiller, T. et al., Science, 2017, 356, 311–315.
- Leszczynska, D., Matuszewska, E., KuczynskaWisnik, D., Furmanek-Blaszk, B. and Laskowska, E., PLoS One, 2013, 8, e54737.
- COVID-19: did preventive restrictions work?
Abstract Views :170 |
PDF Views:74
Authors
Affiliations
1 Abasaheb Garware College, Krave Road, Pune 411 004, IN
2 E-1-8, Girija Shankar Vihar, Karve Nagar, Pune 411 052, IN
1 Abasaheb Garware College, Krave Road, Pune 411 004, IN
2 E-1-8, Girija Shankar Vihar, Karve Nagar, Pune 411 052, IN
Source
Current Science, Vol 122, No 9 (2022), Pagination: 1081-1085Abstract
During the ongoing COVID-19 pandemic, if a preventive restriction (PR) intended to arrest transmission of the virus is effective, we expect a decrease in the rate of transmission. If an effective PR is lifted or relaxed, the reverse is expected. We test this expectation in the history of PR imposition and relaxation in all countries based on available public database using a null model of spontaneous change in the rate of transmission independent of PRs. We use the stringency index defined earlier and available in public database to represent PR in different countries at different times. We found no negative correlation between standing stringency index of PR and change in slope of the local curve. A change in stringency index was significantly negatively correlated with change in slope, but it could explain only 6.1% of the variance in rates of transmission. The distribution of slope changes after imposing versus after relaxing PRs was highly overlapping with only a tail consisting of 4.5% PR impositions being clearly non-overlapping with PR relaxation. Non-parametrically, only 5.9% of PR impositions were associated with a reduction in the slope above the expectation of a null hypothesis. Globally, PRs have played a small role in the pandemic up to March 2021. This feedback needs to be considered in making policies for disease prevention in the further course of the COVID-19 pandemic as well as in any future threats of respiratory disease epidemics.Keywords
COVID-19, epidemiology, lockdown, preventive restrictions, stringency index.References
- Alfano, V. and Ercolano, S., The efficacy of lockdown against COVID-19: a cross-country panel analysis. Appl. Health Econ. Health Policy, 2020, 18(4), 509–517.
- Kharroubi, S. and Saleh, F., Are lockdown measures effective against COVID-19? Front. Public Health, 2020, 8, 549692.
- Atalan, A., Is the lockdown important to prevent the COVID-19 pandemic? Effects on psychology, environment and economyperspective. Ann. Med. Surg., 2020, 56, 38–42.
- Brauner, J. M., Inferring the effectiveness of government interventions against COVID-19. Science, 2020, 371, 6531.
- Krishnan, S., Deo, S. and Manurkar, S., 50 days of lockdown: measuring India’s success in arresting COVID-19. ORF Special Report No. 107, Observer Research Foundation, New Delhi, India, May 2020.
- Meo, S. A., Impact of lockdown on COVID-19 prevalence and mortality during 2020 pandemic: observational analysis of 27 countries. Eur. J. Med. Res., 2020, 25, 56.
- Wibbens, P. D., Koo, W. W.-Y. and McGahan, A. M., Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction. PLoS ONE, 2020, 15(12), e0244177.
- Alfano, V., Ercolano, S. and Cicatiello, L., School openings and the COVID-19 outbreak in Italy. A provincial-level analysis using the synthetic control method. Health Policy, 2021, 125, 1200–1207.
- Ludvigsson, J. F., Open schools, COVID-19 and child and teacher morbidity in Sweden. N. Engl. J. Med., 2021, 384, 7.
- Gupta, M. et al., Transmission dynamics of the COVID-19 epidemic in India and modeling optimal lockdown exit strategies International. J. Infect. Dis., 2021, 103, 579–589.
- Vincetia, M., Lockdown timing and efficacy in controlling COVID-19 using mobile phone tracking. J. Clin. Med., 2020, 25, 100457.
- Pachetti, M. et al., Impact of lockdown on COVID-19 case fatality rate and viral mutations spread in 7 countries in Europe and North America. J. Transl. Med., 2020, 18, 338; https://doi.org/10.1186/ s12967-020-02501-x.
- Han, E. et al., Lessons learnt from easing COVID-19 restrictions: an analysis of countries and regions in Asia Pacific and Europe. Lancet, 2020, 396(10261), 1525–1534.
- Jain, V. et al., Differential mortality in COVID-19 patients from India and Western countries. Diab. Metab. Syndr.: Clin. Res. Rev., 2020, 14, 1037–1041.
- Hale, T. et al., A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker). Nature Hum. Behav., 2021, 5, 529–538; https://doi.org/10.1038/s41562-021-01079-8.
- Haug, N. et al., Ranking the effectiveness of worldwide COVID19 government interventions. Nature Hum. Behav., 2020, 4, 1303– 1312.
- Alfano, V. and Ercolano, S., Stay at home! Governance quality and effectiveness of lockdown. Soc. Indic. Res., 2021, 159(1), 101–123.
- Bargain, O. and Aminjonov, U., Trust and compliance to public health policies in time of COVID-19. J. Public Econ., 2020, 192(1), 104316.
- Smit, A. J., Fitchett, J. M., Engelbrecht, F. A., Scholes, R. J., Dzhivhuho, G. and Sweijd, N. A., Winter is coming: a southern hemisphere perspective of the environmental drivers of SARSCoV-2 and the potential seasonality of COVID-19. Int. J. Environ. Res. Public Health, 2020, 17(16), 5634; https://doi.org/10.3390/ijerph17165634.
- Epstein, J. M., Hatna, E. and Crodelle, J., Triple contagion: a twofears epidemic model. J. R. Soc. Interface, 2021 181, 20210186; doi:10.1098/rsif.2021.0186. Epub. PMID: 34343457; PMCID: PMC8331242.
- Watve, M. et al., Epidemiology: gray immunity model gives qualitatively different predictions; https://www.preprints.org/manuscript/202109.0162/v2.
- Gandhi, M. and Rutherford, G. W., Facial masking for COVID19 – potential for ‘variolation’ as we await a vaccine. N. Engl. J. Med., 2020, 383, 18.
- Greenhalgh, T. et al., Ten scientific reasons in support of airborne transmission of SARS-CoV-2. Lancet, published online 15 April 2021; https://doi.org/10.1016/S0140-6736(21)00869-2.