53 research outputs found
An Analysis of Farmers’ Perception and Awareness towards Crop Insurance as a Tool for Risk Management in Tamil Nadu
To insulate farmers against risks in agriculture, government has launched several schemes such as National Agricultural Insurance Scheme and weather index based crop insurance schemes. But their coverage seems to be limited among the farmers primarily due to lack of full information. This paper has reported the results of a survey of 600 farmers conducted to assess their perception about various facets of crop insurance schemes. The Probit and Tobit models have been employed to analyse the factors affecting awareness among the farmers. Crop diversification index has also been used to examine the farmers’ adjustment mechanism against risks. The survey has revealed that most farmers (65%) are aware of risk mitigation measures of the government. But, only half of the farmers have been found aware about the crop insurance schemes/products. This implies that there is need to disseminate information about insurance schemes across the target groups. Further, it has been shown that factors such as gross cropped area, income from other than agricultural sources, presence of risk in farming, number of workers in the farm family, satisfaction with the premium rate and affordability of the insurance premium amount significantly and positively influence the adoption of insurance and premium paid by the farmers. The study has clearly brought out the urgency of developing more innovative products, having minimum human interventions.Crop insurance, Risk management, Crop diversification index, Agricultural and Food Policy, Q14, Q18,
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Investigating the impact of poverty on colonization and infection with drug-resistant organisms in humans: a systematic review
Background
Poverty increases the risk of contracting infectious diseases and therefore exposure to antibiotics. Yet there is lacking evidence on the relationship between income and non-income dimensions of poverty and antimicrobial resistance. Investigating such relationship would strengthen antimicrobial stewardship interventions.
Methods
A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Ovid, MEDLINE, EMBASE, Scopus, CINAHL, PsychINFO, EBSCO, HMIC, and Web of Science databases were searched in October 2016. Prospective and retrospective studies reporting on income or non-income dimensions of poverty and their influence on colonisation or infection with antimicrobial-resistant organisms were retrieved. Study quality was assessed with the Integrated quality criteria for review of multiple study designs (ICROMS) tool.
Results
Nineteen articles were reviewed. Crowding and homelessness were associated with antimicrobial resistance in community and hospital patients. In high-income countries, low income was associated with Streptococcus pneumoniae and Acinetobacter baumannii resistance and a seven-fold higher infection rate. In low-income countries the findings on this relation were contradictory. Lack of education was linked to resistant S. pneumoniae and Escherichia coli. Two papers explored the relation between water and sanitation and antimicrobial resistance in low-income settings.
Conclusions
Despite methodological limitations, the results suggest that addressing social determinants of poverty worldwide remains a crucial yet neglected step towards preventing antimicrobial resistance
Brevicoryne brassicae aphids interfere with transcriptome responses of Arabidopsis thaliana to feeding by Plutella xylostella caterpillars in a density‑dependent manner
Plants are commonly attacked by multiple herbivorous species. Yet, little is known about transcriptional patterns underlying plant responses to multiple insect attackers feeding simultaneously. Here, we assessed= transcriptomic responses of Arabidopsis thaliana plants to simultaneous feeding by Plutella xylostella caterpillars and Brevicoryne brassicae aphids in comparison to plants infested by P. xylostella caterpillars alone, using microarray analysis. We particularly investigated how aphid feeding interferes with the transcriptomic response to P. xylostella caterpillars and whether this interference is dependent on aphid density and time since aphid attack. Various JA-responsive genes were up-regulated in response to feeding by P. xylostella caterpillars. The additional presence of aphids, both at low and high densities, clearly affected the transcriptional plant response to caterpillars. Interestingly, some important modulators of plant defense signalling, including WRKY transcription factor genes and ABA-dependent genes, were differentially induced in response to simultaneous aphid feeding at low or high density compared with responses to P. xylostella caterpillars feeding alone. Furthermore, aphids affected the P. xylostella-induced transcriptomic response in a density dependent manner, which caused an acceleration in plant response against dual insect attack at high aphid density compared to dual insect attack at low aphid density. In conclusion, our study provides evidence that aphids influence the caterpillar-induced transcriptional response of A. thaliana in a density-dependent manner. It highlights the importance of addressing insect density to understand how plant responses to single attackers interfere with responses to other attackers and thus underlines the importance of the dynamics of transcriptional plant responses to multiple herbivory
From Isotropic to Anisotropic Side Chain Representations: Comparison of Three Models for Residue Contact Estimation
The criterion to determine residue contact is a fundamental problem in deriving knowledge-based mean-force potential energy calculations for protein structures. A frequently used criterion is to require the side chain center-to-center distance or the -to- atom distance to be within a pre-determined cutoff distance. However, the spatially anisotropic nature of the side chain determines that it is challenging to identify the contact pairs. This study compares three side chain contact models: the Atom Distance criteria (ADC) model, the Isotropic Sphere Side chain (ISS) model and the Anisotropic Ellipsoid Side chain (AES) model using 424 high resolution protein structures in the Protein Data Bank. The results indicate that the ADC model is the most accurate and ISS is the worst. The AES model eliminates about 95% of the incorrectly counted contact-pairs in the ISS model. Algorithm analysis shows that AES model is the most computational intensive while ADC model has moderate computational cost. We derived a dataset of the mis-estimated contact pairs by AES model. The most misjudged pairs are Arg-Glu, Arg-Asp and Arg-Tyr. Such a dataset can be useful for developing the improved AES model by incorporating the pair-specific information for the cutoff distance
Towards eco-friendly crop protection: natural deep eutectic solvents and defensive secondary metabolites
Plant science
Decline of Traditional Water Harvesting Systems: Tanks in the Drought-Prone Areas of Andhra Pradesh
Special educators’ experiences of a numeracy intervention for autistic students
Very little qualitative research has been carried out about the experiences of educators who deliver mathematics evidence-based teaching programmes to autistic students. Using a semi-structured format, we interviewed ten educators who had been delivering the Teaching Early Numeracy to Children with Developmental Disabilities (TEN-DD) programme for eight months with autistic students in a special school setting. Reflexive thematic analysis findings indicated that taking part in the numeracy intervention was a valuable experience for both the educators and their students. There was initial scepticism about the intervention, but this was transformed to conviction during the implementation period. Educators reported an increased sense of competence in their teaching skills, evident in greater satisfaction and increased self-efficacy. Furthermore, there was a strong interest in continuing to use the numeracy intervention with students. There were also implementation challenges with TEN-DD, including students’ challenging behavior. The implications of these findings are discussed
An Analysis of Farmers’ Perception and Awareness towards Crop Insurance as a Tool for Risk Management in Tamil Nadu
To insulate farmers against risks in agriculture, government has launched several schemes such as National
Agricultural Insurance Scheme and weather index based crop insurance schemes. But their coverage
seems to be limited among the farmers primarily due to lack of full information. This paper has reported the
results of a survey of 600 farmers conducted to assess their perception about various facets of crop
insurance schemes. The Probit and Tobit models have been employed to analyse the factors affecting
awareness among the farmers. Crop diversification index has also been used to examine the farmers’
adjustment mechanism against risks. The survey has revealed that most farmers (65%) are aware of risk
mitigation measures of the government. But, only half of the farmers have been found aware about the crop
insurance schemes/products. This implies that there is need to disseminate information about insurance
schemes across the target groups. Further, it has been shown that factors such as gross cropped area,
income from other than agricultural sources, presence of risk in farming, number of workers in the farm
family, satisfaction with the premium rate and affordability of the insurance premium amount significantly
and positively influence the adoption of insurance and premium paid by the farmers. The study has clearly
brought out the urgency of developing more innovative products, having minimum human interventions
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