Artificial intelligence-based nonlinear control of renewable energies and storage system in a DC microgrid.

To minimize the global warming and the impact of greenhouse effect, renewable energy sources-based microgrids are widely studied. In this paper, the control of PV, wind-based renewable energy system and battery, supercapacitor-based energy storage system in a DC microgrid have been presented. Maximum power points for PV and wind have been obtained using neural network and optimal torque control, respectively.

A descriptive study of double burden of malnutrition in mothers of children with severe acute malnutrition admitted in Children Hospital and Institute of Child Health, Multan.

Objective: To assess the nutritional status of mothers of severely malnourished children, and to evaluate the factors associated with inadequate caloric intake of children with severe acute malnutrition versus sufficient caloric intake by mothers.

Methods: The cross-sectional descriptive study was conducted from January to June 2016 at Children Hospital and Institute of Child Health, Multan, Pakistan, and comprised mothers of severely malnourished children admitted for treatment. Data was collected using a questionnaire administered through interviews.