Water Network Optimization with Wastewater Regeneration Models

The conventional water network synthesis approach greatly simplifies wastewater treatment units by using fixed recoveries, creating a gap for their applicability to industrial processes. This work describes a unifying approach combining various technologies capable of removing all the major types of contaminants through the use of more realistic models. The following improvements are made over the typical superstructure-based water network models. First, unit-specific shortcut models are developed in place of the fixed contaminant removal model to describe contaminant mass transfer in wastewater treatment units. Shortcut wastewater treatment cost functions are also incorporated into the model. In addition, uncertainty in mass load of contaminants is considered to account for the range of operating conditions. Furthermore, the superstructure is modified to accommodate realistic potential structures. We present a modified Lagrangean-based decomposition algorithm in order to solve the resulting nonconvex mixed-integer nonlinear programming (MINLP) problem efficiently. Several examples are presented to illustrate the effectiveness and limitations of the algorithm for obtaining the global optimal solutions.The authors would like to acknowledge financial support from the National Science Foundation for financial support under grant CBET-1437668, the program “Estancias de movilidad en el extranjero “Jose Castillejo” para jóvenes doctores” (JC2011-0051) of the Spanish Ministerio de Educación, and from the University of Alicante (GRE11-19)

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology

Game feature and expertise effects on experienced richness, control and engagement in game play

The extent to which game play is experienced as engaging is an important criterion for the playability of video games. This study investigates how video games can be designed towards increased levels of experienced engagement over time. For this purpose, two experiments were conducted in which a total of 35 participants repeatedly played a video game. Results indicate that experienced engagement is based on the extent to which the game provides rich experiences as well as by the extent to which the game provides a sense of control. In view of the influence of both game features and players’ expertise on the levels of experienced richness and control, it is concluded that game features should be modified over time to maintain optimal levels of engagement