Abstract: The question of legal liability over injury arising out
of the import and the introduction of GM food emerges as a crucial
issue confronting to promote GM food and its derivatives. There is a
greater possibility of commercialized GM food from the exporting
country to enter importing country where status of approval shall not
be same. This necessitates the importance of fixing a liability
mechanism to discuss the damage, if any, occurs at the level of
transboundary movement or at the market. There was a widespread consensus to develop the Cartagena
Protocol on Biosafety and to give for a dedicated regime on liability
and redress in the form of Nagoya Kuala Lumpur Supplementary
Protocol on the Liability and Redress (‘N-KL Protocol’) at the
international context. The national legal frameworks based on this
protocol are not adequately established in the prevailing food
legislations of the developing countries. The developing economy
like India is willing to import GM food and its derivatives after the
successful commercialization of Bt Cotton in 2002. As a party to the
N-KL Protocol, it is indispensable for India to formulate a legal
framework and to discuss safety, liability, and regulatory issues
surrounding GM foods in conformity to the provisions of the
Protocol. The liability mechanism is also important in the case where
the risk assessment and risk management is still in implementing
stage. Moreover, the country is facing GM infiltration issues with its
neighbors Bangladesh. As a precautionary approach, there is a need
to formulate rules and procedure of legal liability to discuss any kind
of damage occurs at transboundary trade. In this context, the
proposed work will attempt to analyze the liability regime in the
existing Food Safety and Standards Act, 2006 from the applicability
and domestic compliance and to suggest legal and policy options for
regulatory authorities.
Abstract: Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.