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Biomedical signals transmitted over the internet are usually tagged with patient information. Data hiding techniques such as steganography ensures the security of such data by hiding the data into signals. However, data hiding results in signal deterioration that might affect diagnosability. A novel technique which uses curvelet transforms to hide patient information into their ECG signal is presented. Curvelet transform decomposes the ECG signal into frequency sub-bands. A quantisation approach is used to embed patient data into coefficients whose values are around zero, in the high-frequency subband. Performance metrics provide the measure of watermark imperceptibility of the proposed approach. BER is used to measure the ability to extract patient data. The proposed approach is demonstrated on the MIT-BIH database and the observations validate that its performance is superior compared with the random locations approach. Although the performance of the proposed approach decreases as patient information size increases, the peak signal-to-noise ratio values are high. Therefore, the proposed approach can be used for the safe transfer of patient data.

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A number of compounds have been prepared in order to improve pharmacological roles of antihyperglycemic activity. In the present paper, a series of 3-benzyl-2-(4'-substituted phenyl)-4(5H)-(4″-nitrophenyl amino)-1,3-oxazolidines (6a-e) were tested against hyperglycemia. Their antihyperglycemic activity was evaluated by streptozotocin (STZ) and sucrose-loaded (SLM) models. Compounds 6a, b, c, d, and e displayed significant reductions in blood glucose in the streptozotocin and sucrose loaded rat models. The purity of the synthesized compounds was characterized by means of IR, (1)H-NMR, mass spectral and elemental analysis.

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While planning resource management systems in rural areas, it is important to consider criteria that are specific to the local social conditions. Such criteria might change from one region to another and are hence best identified using a participatory approach. In this work, we propose a participatory framework to identify such criteria and derive their weights. These identified criteria and their weights are used as parameters to develop a quantitative model for evaluating efficiency of each system. Such a model can serve as a support tool for stakeholders to simulate and analyze “what‐if” scenarios, evaluate alternatives, and select one which best satisfies their requirements. We use existing systems to test the model by comparing efficiencies evaluated by the model to efficiencies perceived by the stakeholders. The model is calibrated by repeating the process until statistically significant correlation is achieved between evaluated and perceived efficiencies. The novelty of the proposed framework lies in treating efficiencies perceived by the stakeholders as the ground truth since they know these systems well and are their ultimate users. The framework is successfully demonstrated using case study of rainwater harvesting (RWH) systems in an Indian village. The resulting calibrated model can be used to plan new RWH systems in this region and similar regions elsewhere. The framework can be used to plan other resource management systems in various regions.