Emerging Markets for GM Foods: An Indian Perspective on Consumer Understanding and Willingness to Pay

This paper addresses the issues of consumer awareness, opinion, acceptance and willingness to pay for GM foods in the Indian market. A random utility approach is used to estimate a logit equation which indicates what factors affect the likelihood of consumption of non-GM and GM foods and whether or not consumers are willing to pay a premium for non-GM/GM foods. Data was generated through questionnaire survey which was administered to 602 respondents in the city of Ahmedabad and 110 respondents on internet. More than 90% of the respondents from the city survey did not know about GM foods. However, after informing them about the pros and cons of GM foods, more than 70% were willing to consume even if GM and non-GM foods were available for the same price. Ceteris paribus as the price difference between non-GM and GM food rose, people were more likely to consume GM foods. Likelihood of GM food consumption seemed to increase as one moved from very poor and not-so-poor income brackets to higher income brackets. Being a female or a joint family member increased the likelihood of choosing non-GM rice and edible oil. On an average, consumers were willing to pay 19.5% and 16.12% premiums for golden rice and GM edible oil, respectively. Overall, it appears that GM foods will be acceptable in the Indian market. However, consumer education societies, government ministries, and food companies may have to create awareness about the GM foods among Indian consumers.

Emerging Markets for GM Foods: A Study of Consumer's Willingness to Pay in India

A random utility approach is used to estimate logit equations which indicate what factors affect the likelihood of consumption of non-GM and GM foods, and, whether or not consumers are willing to pay a premium for non-GM/GM foods. Ceteris paribus as the price difference between non-GM and GM food rose, people were more likely to consume GM foods. Likelihood of GM food consumption was higher in the middle income brackets. Consumers were willing to pay an expected premium of 19.5% and 16.12% for golden rice and GM edible oil respectively. In case of chicken, consumers seemed to pay a very negligible premium for non-GM fed chicken. Overall, it appears that GM foods may be acceptable in the Indian market. However, basic awareness about the GM foods may have to be created among the consumers through government ministries, consumer interest groups, and biotech food-crop companies.GM Foods, Golden Rice, Bt cottonseed oil, GM fed chicken, Willingness to Pay, Random utility approach, Logit, India., Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, Q13, D12,

Interrater reliability in visual identification of interictal high-frequency oscillations on electrocorticography and scalp EEG.

High-frequency oscillations (HFOs), including ripples (Rs) and fast ripples (FRs), are promising biomarkers of epileptogenesis, but their clinical utility is limited by the lack of a standardized approach to identification. We set out to determine whether electroencephalographers experienced in HFO analysis can reliably identify and quantify interictal HFOs. Two blinded raters independently reviewed 10 intraoperative electrocorticography (ECoG) samples from epilepsy surgery cases, and 10 scalp EEG samples from epilepsy monitoring unit evaluations. HFOs were visually marked using bandpass filters (R, 80-250 Hz; FR, 250-500 Hz) with a sampling frequency of 2,000 Hz. There was agreement as to the presence or absence of epileptiform discharges (EDs), Rs, and FRs, in 17, 18, and 18 cases, respectively. Interrater reliability (IRR) was favorable with κ = 0.70, 0.80, and 0.80, respectively, and similar for ECoG and scalp electroencephalography (EEG). Furthermore, interclass correlation for rates of Rs (0.99, 95% confidence interval [CI] 0.96-0.99) and FRs (0.77, 95% CI 0.41-0.91) were superior in comparison to EDs (0.37, 95% CI -0.60 to 0.75). Our data suggest that HFO identification and quantification are reliable among experienced electroencephalographers. Our findings support the reliability of utilizing HFO data in both research and clinical arenas

Effect of magnetic field on the buoyancy and thermocapillary driven convection of an electrically conducting fluid in an annular enclosure

The main objective of this article is to study the effect of magnetic field on the combined buoyancy and surface tension driven convection in a cylindrical annular enclosure. In this study, the top surface of the annulus is assumed to be free, and the bottom wall is insulated, whereas the inner and the outer cylindrical walls are kept at hot and cold temperatures respectively. The governing equations of the flow system are numerically solved using an implicit finite difference technique. The numerical results for various governing parameters of the problem are discussed in terms of the streamlines, isotherms. Nusselt number and velocity profiles in the annuli. Our results reveal that, in tall cavities, the axial magnetic field suppresses the surface tension flow more effectively than the radial magnetic field, whereas, the radial magnetic field is found to be better for suppressing the buoyancy driven flow compared to axial magnetic field. However, the axial magnetic field is found to be effective in suppressing both the flows in shallow cavities. From the results, we also found that the surface tension effect is predominant in shallow cavities compared to the square and tall annulus. Further, the heat transfer rate increases with radii ratio, but decreases with the Hartmann number. (c) 2010 Elsevier Inc. All rights reserved

Pharmacoeconomic analysis of drug expenditure in government medical college and hospital, Vijayawada, India

Background: To conduct economic analysis in tertiary care hospital with a view to identify the categories of drugs needing stringent management control.Methods: The annual consumption and expenditure data is obtained from the drug store of government general hospital, Vijayawada, for the period of April 2015 to March 2016. ABC-VED analysis of the drugs are done based on cost and criticality criteria respectively. ABC-VED matrix analysis was done to classify drugs into category I, II, III.Results: The total annual drug expenditure incurred on 299 drug items for the year 2015-2016 was found to be Rs:4,47,04,446. On ABC analysis, 4%, 9.36%, 86.64% of drugs were found to be Always, Better, and Control category items respectively, amounting to 68.92%, 20.05%, 11.03% of annual drug expenditure. VED analysis showed that 32.10%, 45.5%, 22.4% of drug items were Vital, Essential, and Desirable category items respectively, amounting to 35.3%, 37.1%, 27.6% of annual drug expenditure respectively. By ABC-VED matrix analysis, 34.11%, 46.49%, 19.4% of drug items were found to be category I (high stringent), II (medium stringent), III (low stringent) respectively, amounting to 80.76%, 17.46%, 1.77% of annual drug expenditure respectively.Conclusions: The study identified 34.11% of drug items belonging to category I which require high priority monitoring. Inventory management tools must be routinely used for the better control and judicious use of the resources

METHOD DEVELOPMENT AND VALIDATION OF TIVOZANIB BY USING RP-HPLC IN BULK AND PHARMACEUTICAL DOSAGE FORM

Objective: The current investigation was pointed at developing and progressively validating novel, simple, responsive and stable RP-HPLC method for the measurement of active pharmaceutical ingredient of Tivozanib. Methods: A simple, selective, validated and well-defined stability that shows isocratic RP-HPLC methodology for the quantitative determination of Tivozanib. The chromatographic strategy utilized X-bridge phenyl column of dimensions 150x4.6 mm, 3.5 micron, using isocratic elution with a mobile phase of acetonitrile and 0.1 percent formic acid (50:50). A flow rate of 1 ml/min and a detector wavelength of 216 nm utilizing the PDA detector were given in the instrumental settings. Validation of the proposed method was carried out according to an international conference on harmonization (ICH) guidelines. Results: LOD and LOQ for the two active ingredients were established with respect to test concentration. The calibration charts plotted were linear with a regression coefficient of R2>0.999, means the linearity was within the limit. Recovery, specificity, linearity, accuracy, robustness, ruggedness were determined as a part of method validation and the results were found to be within the acceptable range. Conclusion: The proposed method to be fast, simple, feasible and affordable in assay condition. During stability tests, it can be used for routine analysis of the selected drugs

Deep Learning Meets Mechanism Design: Key Results and Some Novel Applications

Mechanism design is essentially reverse engineering of games and involves inducing a game among strategic agents in a way that the induced game satisfies a set of desired properties in an equilibrium of the game. Desirable properties for a mechanism include incentive compatibility, individual rationality, welfare maximisation, revenue maximisation (or cost minimisation), fairness of allocation, etc. It is known from mechanism design theory that only certain strict subsets of these properties can be simultaneously satisfied exactly by any given mechanism. Often, the mechanisms required by real-world applications may need a subset of these properties that are theoretically impossible to be simultaneously satisfied. In such cases, a prominent recent approach is to use a deep learning based approach to learn a mechanism that approximately satisfies the required properties by minimizing a suitably defined loss function. In this paper, we present, from relevant literature, technical details of using a deep learning approach for mechanism design and provide an overview of key results in this topic. We demonstrate the power of this approach for three illustrative case studies: (a) efficient energy management in a vehicular network (b) resource allocation in a mobile network (c) designing a volume discount procurement auction for agricultural inputs. Section 6 concludes the paper