Senna siamea (yellow cassia).

2021 ◽  
Author(s):  
Julissa Rojas-Sandoval ◽  
Pedro Acevedo-Rodríguez ◽  
Nick Pasiecznik
Keyword(s):  
Tamil Nadu ◽  
Agricultural Land ◽  
Santalum Album ◽  
Indian States ◽  
Senna Siamea ◽  
Shade Tree ◽  
Major Disadvantage ◽  
Dry Zone ◽  
Strong Winds ◽  
Timber Plantations

Abstract S. siamea is indigenous to southern India, Sri Lanka, Malaysia, Cambodia, Thailand and Myanmar, although it has been introduced widely into many states of India and also many countries in tropical Africa. As well as producing a good quality timber, often used for marquetry and inlay work due to its fine figure, the tree is used for erosion control planting, windbreaks, as a host for sandalwood (Santalum album), and as a nurse crop for Swietenia mahogani, to reduce borer attack. It is a common shade tree in Philippine towns and cities. It has been used to revegetate degraded agricultural land and is planted in taungya systems. It may be used as a shade tree for coffee (Heinsleigh and Holaway, 1988).It is one of the chief afforestation species in the dry zone of the Indian states of Andhra Pradesh, Tamil Nadu and Karnataka. The major disadvantage of the species is that it has a shallow root system, which make it susceptible to strong winds. Wood sawdust can cause irritation when in contact with the skin. Trials for timber plantations have been recommended (Gutteridge, 1997; Sosef et al., 1998), particularly as S. siamea could combine timber production with ornamental value. Research on genetic variation to determine the extent of adaptation of various provenances would also be of value.

scholarly journals Interstate disparities in the performances in combatting COVID-19 in India: efficiency estimates across states

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Shrabanti Maity ◽  
Nandini Ghosh ◽  
Ummey Rummana Barlaskar
Keyword(s):  
Disease Management ◽  
Recovery Rate ◽  
Tamil Nadu ◽  
Health Determinants ◽  
Stochastic Production Frontier ◽  
Exogenous Variables ◽  
Indian States ◽  
Secondary Sources ◽  
Comparative Efficiency ◽  
Long Run

Abstract Background Currently, the novel coronavirus or COVID-19 pandemic poses the greatest global health threat worldwide, and India is no exception. As an overpopulated developing country, it is very difficult to maintain social distancing to restrict the spread of the disease in India. Under these circumstances, it is necessary to examine India’s interstate performances to combat COVID-19. This study aims to explore twin objectives: to investigate the comparative efficiency of Indian states to combat COVID-19 and to unfold the factors responsible for interstate disparities in the efficiency in combatting COVID-19. Methods The stochastic production frontier model was utilized for data analysis. The empirical analysis was facilitated by the inefficiency effects model, revealing the factors that influence interstate variability in disease management efficiency. Three types of variables, namely, output, inputs, and exogenous, were used to measure health system efficiency. The relevant variables were compiled from secondary sources. The recovery rate from COVID-19 was the output variable and health infrastructures were considered as the input variable. On the contrary, the non-health determinants considered to have a strong influence on the efficiency of states’ disease management, but could not be considered as input variables, were recognised as exogenous variables. These exogenous variables were specifically used for the inefficiency analysis. Results The empirical results demonstrated the existence of disparities across Indian states in the level of efficiency in combatting COVID-19. A non-trivial outcome of this study was that Tamil Nadu was the best performer and Manipur was the worst performer of the investigated states. Variables such as elderly people, sex ratio, literacy rate, population density, influenced the efficiency of states, and thus, affected the recovery rate. Conclusion This study argues for the efficient utilisation of the existing health infrastructures in India. Simultaneously, the study suggests improving the health infrastructure to achieve a long-run benefit.

scholarly journals Incidence of treatment for postabortion complications in India, 2015

2020 ◽  
Vol 5 (7) ◽  
pp. e002372
Author(s):  
Susheela Singh ◽  
Rubina Hussain ◽  
Chander Shekhar ◽  
Rajib Acharya ◽  
Melissa Stillman ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Large Scale ◽  
National Level ◽  
Uttar Pradesh ◽  
Primary Source ◽  
Reproductive Age ◽  
Legal Abortion ◽  
Indian States ◽  
Medication Abortion ◽  
Postabortion Care

Abortion has been legal under broad criteria in India since 1971. However, access to legal abortion services remains poor. In the past decade, medication abortion (MA) has become widely available in India and use of this method outside of health facilities accounts for over 70% of all abortions. Morbidity from unsafe abortion remains an important health issue. The informal providers who are the primary source of MA may have poor knowledge of the method and may offer inadequate or inaccurate advice on use of the method. Misuse of the method can result in women seeking treatment for true complications as well as during the normal processes of MA. An estimated 5% of all abortions are done using highly unsafe methods and performed by unskilled providers, also contributing to abortion morbidity. This paper provides new representative abortion-related morbidity measures at the national and subnational levels from a large-scale 2015 study of six Indian states—Assam, Bihar, Gujarat, Madhya Pradesh, Tamil Nadu and Uttar Pradesh. The outcomes include the number and treatment rates of women with complications resulting from induced abortion and the type of complications. The total number of women treated for abortion complications at the national level is 5.2 million, and the rate is 15.7 per 1000 women of reproductive age per year. In all six study states, a high proportion of all women receiving postabortion care were admitted with incomplete abortion from use of MA—ranging from 33% in Tamil Nadu to 65% in Assam. The paper fills an important gap by providing new evidence that can inform policy-makers and health planners at all levels and lead to improvements in the provision of postabortion care and legal abortion services—improvements that would greatly reduce abortion-related morbidity and its costs to Indian women, their families and the healthcare system.

scholarly journals Collective and Organic Farming in Tamil Nadu: Women’s Participation, Empowerment and Food Sovereignty

2016 ◽  
Vol 12 (8) ◽  
pp. 184 ◽  
Author(s):  
Dhruv Pande ◽  
Munmun Jha
Keyword(s):  
Organic Farming ◽  
State Government ◽  
Tamil Nadu ◽  
Agricultural Land ◽  
Food Sovereignty ◽  
The State ◽  
Women Farmers ◽  
Women's Participation ◽  
Marginalized Women

<p>The aim of this paper is to explore the notion of women’s participation, empowerment and food sovereignty among the marginalized women farmers in the state of Tamil Nadu in India. The women farmers who belong largely to the so-called lower castes have been marginalized due to the persistent presence of the patriarchal structure and the continued oppression and discrimination in a caste-ridden society. This is supported and supplemented by the policies and politics of globalization through the state apparatus. This research, based on the fieldwork method, highlights the hitherto undermined role of women farmers in the wake of their efforts at establishing enhanced and sustainable socio-economic relations in connection with the local agricultural land which accounts for their economic and social independence and sovereignty, especially food sovereignty. The process marking this transformation includes collective and organic farming based on millets leading to the creation of an inherent and integral food sovereignty vis-a-vis the increasing usurpation of agricultural land through the nexus of the state government and private companies. The paper also analyzes the issue of land ownership, litigation cases involving women, and the role of community organizations which impel the hitherto marginalized women towards self-sustainable, self-sufficient and self-governed environment in rural agricultural economy.</p>

scholarly journals Epidemiology and transmission dynamics of COVID-19 in two Indian states

2020 ◽  
Author(s):  
Ramanan Laxminarayan ◽  
Brian Wahl ◽  
Shankar Reddy Dudala ◽  
K Gopal ◽  
Chandra Mohan ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Andhra Pradesh ◽  
Case Fatality ◽  
Control Measures ◽  
Contact Tracing ◽  
Primary Data ◽  
Indian States ◽  
Middle Income ◽  
Time To Death ◽  
Middle Income Countries

Although most COVID-19 cases have occurred in low-resource countries, there is scarce information on the epidemiology of the disease in such settings. Comprehensive SARS-CoV-2 testing and contact-tracing data from the Indian states of Tamil Nadu and Andhra Pradesh reveal stark contrasts from epidemics affecting high-income countries, with 92.1% of cases and 59.7% of deaths occurring among individuals <65 years old. The per-contact risk of infection is 9.0% (95% confidence interval: 7.5-10.5%) in the household and 2.6% (1.6-3.9%) in the community. Superspreading plays a prominent role in transmission, with 5.4% of cases accounting for 80% of infected contacts. The case-fatality ratio is 1.3% (1.0-1.6%), and median time-to-death is 5 days from testing. Primary data are urgently needed from low- and middle-income countries to guide locally-appropriate control measures.

scholarly journals Screening of South Indian Culinary Melon (Cucumis melo subsp. agrestis var. acidulus) Accessions for Downy Mildew Disease under Natural Epiphytotic Condition

2021 ◽  
Vol 8 (4) ◽  
pp. 211-216
Author(s):  
Ratnakar M. Shet ◽  
◽  
A. Prashantha ◽  
P. S. Mahanthesh ◽  
K. S. Sankarappa ◽  
...  
Keyword(s):  
Downy Mildew ◽  
Cucumis Melo ◽  
Tamil Nadu ◽  
Indian Subcontinent ◽  
Indian States ◽  
South Indian ◽  
The Family ◽  
Percent Disease Index ◽  
Moderately Resistant ◽  
Downy Mildew Disease

Culinary melon also known as non dessert cucumber (Cucumis melo subsp. agrestis var. acidulus) belongs to the family Cucurbitaceae. It is widely cultivated in Southern parts of Indian subcontinent. It is mainly utilized for preparation of lentil soup, sambar, dosa, palya and chutney. 70 accessions were collected from six South Indian states namely Karnataka, Kerala, Andhra Pradesh, Tamil Nadu, Telangana and Goa. The accessions were evaluated for incidence of downy mildew resistance during Kharif 2018 under natural condition. The percent disease index (PDI) for downy mildew ranged from 3.70 to 48.64%. 10 accessions showed resistance to downy mildew. Among them, accession MS21 showed resistance with average least PDI of 3.70 followed by MS 6 (6.54). 50 accessions were found to be moderately resistant with average PDI ranging from 20 to 39.80. 12 accessions were found susceptible with PDI ranging from 41 to 49. None of the accession was found highly susceptible to the disease. The resistant accessions can be utilized as donor parents for resistant breeding in the improvement of culinary melon as well as melon group of vegetables.

scholarly journals “He made me fall at the feet of a woman”: Masculine Anxieties and Dysfunctional Romance in Tamil Cult Film Subramaniyapuram (2008)

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Divya A ◽  
Keyword(s):  
Tamil Nadu ◽  
Hegemonic Masculinity ◽  
Female Identity ◽  
Critical Discourse ◽  
Indian States ◽  
Tamil Cinema ◽  
Point Of Departure

Tamil Cinema is “one of India’s largest, most prolific and increasingly significant cinemas” (Velayutham 2008, pp.1-2). Madurai genre in Tamil films is popularly known as 3M films (Murder, Mayhem and Madurai) (Damodaran Gorringe 2017, p.9). Subramaniyapuram (Sasikumar, 2008) is a Madurai film that attained cult status in both the Indian states of Tamil Nadu and Kerala since its release in 2008. A collection of essays on Subramaniyapuram edited by anthropologist Anand Pandian was published in 2013, a rare honour to be bestowed on a Tamil film in recent times. Significantly, the film’s problematic gender narrative—especially the entangled relation between the romantic plot and the masculine “plots”—is not the central subject of exploration of any of the essays in this edited collection, nor has it been discussed in depth in any critical discourse on the film so far. In this article, using Laura Mulvey’s theoretical lens as a point of departure, I argue that the female identity is crucial to the narrative functioning of the various plots of Subramaniyapuram. The film’s ultimate narrative desires, I illustrate, are in affirmation of masculine supremacy, hegemonic masculinity, and the women as femme fatales.

scholarly journals Estimating global land system impacts of timber plantations using MAgPIE 4.3.5

2021 ◽  
Vol 14 (10) ◽  
pp. 6467-6494
Author(s):  
Abhijeet Mishra ◽  
Florian Humpenöder ◽  
Jan Philipp Dietrich ◽  
Benjamin Leon Bodirsky ◽  
Brent Sohngen ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Agricultural Land ◽  
Timber Production ◽  
Land Resources ◽  
Natural Forests ◽  
Land Use Patterns ◽  
Land System ◽  
Land Use Dynamics ◽  
Timber Plantations

Abstract. Out of 1150 Mha (million hectares) of forest designated primarily for production purposes in 2020, plantations accounted for 11 % (131 Mha) of this area and fulfilled more than 33 % of the global industrial roundwood demand. However, adding additional timber plantations to meet increasing timber demand intensifies competition for scarce land resources between different land uses such as food, feed, livestock and timber production. Despite the significance of plantations with respect to roundwood production, their importance in meeting the long-term timber demand and the implications of plantation expansion for overall land-use dynamics have not been studied in detail, in particular regarding the competition for land between agriculture and forestry in existing land-use models. This paper describes the extension of the modular, open-source land system Model of Agricultural Production and its Impact on the Environment (MAgPIE) using a detailed representation of forest land, timber production and timber demand dynamics. These extensions allow for a better understanding of the land-use dynamics (including competition for land) and the associated land-use change emissions of timber production. We show that the spatial cropland patterns differ when timber production is accounted for, indicating that timber plantations compete with cropland for the same scarce land resources. When plantations are established on cropland, it causes cropland expansion and deforestation elsewhere. Using the exogenous extrapolation of historical roundwood production from plantations, future timber demand and plantation rotation lengths, we model the future spatial expansion of forest plantations. As a result of increasing timber demand, we show a 177 % increase in plantation area by the end of the century (+171 Mha in 1995–2100). We also observe (in our model results) that the increasing demand for timber amplifies the scarcity of land, which is indicated by shifting agricultural land-use patterns and increasing yields from cropland compared with a case without forestry. Through the inclusion of new forest plantation and natural forest dynamics, our estimates of land-related CO2 emissions better match with observed data, in particular the gross land-use change emissions and carbon uptake (via regrowth), reflecting higher deforestation with the expansion of managed land and timber production as well as higher regrowth in natural forests and plantations.

scholarly journals Crop Yield Prediction using XG Boost Algorithm

2020 ◽  
Vol 8 (5) ◽  
pp. 3516-3520
Keyword(s):  
Crop Yield ◽  
Tamil Nadu ◽  
Crop Yields ◽  
Absolute Error ◽  
Climatic Conditions ◽  
Support Vector ◽  
Yield Prediction ◽  
Indian States ◽  
South Indian ◽  
Proposed Model

The main objective of this research is to predict crop yields based on cultivation area, Rainfall and maximum and minimum temperature data. It will help our Indian farmers to predict crop yielding according to the environment conditions. Nowadays, Machine learning based crop yield prediction is very popular than the traditional models because of its accuracy. In this paper, linear regression, Support Vector Regression, Decision Tree and Random forest is compared with XG Boost algorithm. The above mentioned algorithms are compared based on R2 , Minimum Square Error and Minimum Absolute Error. The dataset is prepared from the data.gov.in site for the year from 2000 to 2014. The data for 4 south Indian states Andhra Pradesh, Karnataka, Tamil Nadu and Kerala data alone is taken since all these states has same climatic conditions. The proposed model in this paper based on XG Boost is showing much better results than other models. In XG Boost R2 is 0.9391 which is the best when compared with other models.

scholarly journals COVID-19 Epidemic Forecast in Different States of India using SIR Model

2020 ◽  
Author(s):  
Mukesh Jakhar ◽  
P K Ahluwalia ◽  
Ashok Kumar
Keyword(s):  
Tamil Nadu ◽  
Reproduction Number ◽  
Epidemiological Data ◽  
Final Phase ◽  
Statistical Parameters ◽  
Indian States ◽  
Infected People ◽  
Epidemic Curve ◽  
Epidemic Size ◽  
Final Epidemic Size

The epidemiological data up to 12th May 2020 for India and its 24 states has been used to predict COVID-19 outbreak within classical SIR (Susceptible-Infected-Recovered) model. The basic reproduction number R0 of India is calculated to be 1.15, whereas for various states it ranges from 1.03 in Uttarakhand to 7.92 in Bihar. The statistical parameters for most of the states indicates the high significance of the predicted results. It is estimated that the epidemic curve flattening in India will start from the first week of July and epidemic may end in the third week of October with final epidemic size ~1,75,000. The epidemic in Kerala is in final phase and is expected to end by first week of June. Among Indian states, Maharashtra is severely affected where the ending phase of epidemic may occur in the second week of September with epidemic size of ~55,000. The model indicates that the fast growth of infection in Punjab is from 27th April 2020 to 2nd June 2020, thereafter, curve flattening will start and the epidemic is expected to finished by the first week of July with the estimated number of ~3300 infected people. The epidemic size of COVID-19 outbreak in Delhi, West Bengal, Gujrat, Tamil Nadu and Odisha can reach as large as 24,000, 18,000, 16,000, 13,000 and 11,000, respectively, however, these estimations may be invalid if large fluctuation of data occurs in coming days.

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