A multi-period optimization model for energy planning with CO(2) emission consideration.

A novel deterministic multi-period mixed-integer linear programming (MILP) model for the power generation planning of electric systems is described and evaluated in this paper. The model is developed with the objective of determining the optimal mix of energy supply sources and pollutant mitigation options that meet a specified electricity demand and CO(2) emission targets at minimum cost. Several time-dependent parameters are included in the model formulation; they include forecasted energy demand, fuel price variability, construction lead time, conservation initiatives, and increase in fixed operational and maintenance costs over time. The developed model is applied to two case studies. The objective of the case studies is to examine the economical, structural, and environmental effects that would result if the electricity sector was required to reduce its CO(2) emissions to a specified limit.

Design of Chronomodulated Drug Delivery System of Valsartan: In Vitro Characterization.

The aim of the present study was to design and evaluate a chronomodulated time-clock pulsatile tablets of valsartan to release it after a certain lag time, independent of the gastrointestinal pH, in its absorption window to cope with the circadian rhythm of human body for blood pressure elevation. Core tablets were prepared by direct compression of a homogenous mixture of valsartan, Avicel PH101, croscarmellose sodium, magnesium stearate and Aerosil. The core tablets were then sprayed coated with a sealing layer formed of ethyl cellulose that was subsequently coated with a release-controlling layer. Three different aqueous dispersions namely; carnauba wax or beeswax or a mixture in a ratio of 2.5:1, respectively, were used to form five time-clock tablet formulations having the release controlling layer with different thickness {B5, B10, B20, BW5 and CW5}. Quality control testing were carried out to the core tablets. Differential scanning calorimetry was also performed to detect the possible drug excipient interaction in the core tablet formulation. The release was carried out, for the prepared time-clock tablet formulations, in 0.1 N hydrochloric acid for the first 2 h, followed by phosphate buffer (pH 6.8) for 4.5 h. The effect of pH on valsartan release was studied through a release study in 0.1 N hydrochloric acid for 6.5 h. Two phase dissolution study was performed to the selected time-clock tablet formulation to predict the drug permeation through the gastrointestinal tract. Stability study of the selected formula was performed at 25°/60% RH and at 40°/75% RH for 3 months. Results showed that a release-controlling layer composed of a mixture of carnauba wax and beeswax in a ratio of 2.5:1 showed a reasonable release lag time. The release lag time of the tablets increased with the increase of the coat thickness, thus B20>B10>B5 with corresponding lag time values of 4.5, 3 and 2.5 h, respectively. Selected B5 tablet formula exhibited a reasonable lag time after which the highest, complete % drug release at pH 6.8 was obtained. In addition, a good partitioning of valsartan, between the aqueous and organic phases in a ratio of 1:7, was observed. The selected formula was stable for at least 3 months under standard long-term and accelerated storage conditions. In conclusion, in vitro studies revealed that the novel time-clock system could be used successfully to deliver valsartan in a pulsatile pH-independent manner. It provided a desirable lag time followed by a rapid and complete drug release accompanied by an expected effective permeation through the biological membranes upon release in the duodenum; the window of absorption, as indicated by the two phase release study.

A heuristic optimization approach for Air Quality Monitoring Network design with the simultaneous consideration of multiple pollutants.

An interactive optimization methodology for allocating the number and configuration of an Air Quality Monitoring Network (AQMN) in a vast area to identify the impact of multiple pollutants is described. A mathematical model based on the multiple cell approach (MCA) was used to create monthly spatial distributions for the concentrations of the pollutants emitted from different emission sources. These spatial temporal patterns were subject to a heuristic optimization algorithm to identify the optimal configuration of a monitoring network. The objective of the optimization is to provide maximum information about multi-pollutants (i.e., CO, NO(x) and SO(2)) emitted from each source within a given area. The model was applied to a network of existing refinery stacks and the results indicate that three stations can provide a total coverage of more than 70%. In addition, the effect of the spatial correlation coefficient (R(C)) on total area coverage was analyzed. The modeling results show that as the cutoff correlation coefficient R(C) is increased from 0.75 to 0.95, the number of monitoring stations required for total coverage is increased. A high R(C) based network may not necessarily cover the entire region, but the covered region will be well represented. A low R(C) based network, on the other hand, would offer more coverage of the region, but the covered region may not be satisfactorily represented.