The confirmation of the Cabibbo-suppressed charm baryon decay mode {Lambda}{sub c}{sup +} {yields} p{pi}{sup +}{pi}{sup -} is reported. All data analyzed are from SELEX, a fixed target experiment at Fermilab that took data during 1996 and 1997, mainly with a 600 GeV/c {Sigma}{sup -} beam. The branching ratio of the Cabibbo-suppressed decay mode {Lambda}{sub c}{sup +} {yields} p{pi}{sup +}{pi}{sup -} relative to the Cabibbo-favored mode {Lambda}{sub c}{sup +} {yields} pK{sup -}{pi}{sup +} is measured to be: {Gamma}({Lambda}{sub c}{sup +} {yields} p{pi}{sup +}{pi}{sup -})/{Gamma}({Lambda}{sub c}{sup +} {yields} pK{sup -}{pi}{sup +}) = 0.103 {+-} 0.022.

In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.