Chip and Signature Interleaving in DS CDMA Systems

Siirretty Doriast

Structure-based Prediction of Protein-protein Interaction Networks across Proteomes

Protein-protein interactions (PPIs) orchestrate virtually all cellular processes, therefore, their exhaustive exploration is essential for the comprehensive understanding of cellular networks. Significant efforts have been devoted to expand the coverage of the proteome-wide interaction space at molecular level. A number of experimental techniques have been developed to discover PPIs, however these approaches have some limitations such as the high costs and long times of experiments, noisy data sets, and often high false positive rate and inter-study discrepancies. Given experimental limitations, computational methods are increasingly becoming important for detection and structural characterization of PPIs. In that regard, we have developed a novel pipeline for high-throughput PPI prediction based on all-to-all rigid body docking of protein structures. We focus on two questions, ‘how do proteins interact?’ and ‘which proteins interact?’. The method combines molecular modeling, structural bioinformatics, machine learning, and functional annotation data to answer these questions and it can be used for genome-wide molecular reconstruction of protein-protein interaction networks. As a proof of concept, 61,913 protein-protein interactions were confidently predicted and modeled for the proteome of E. coli. Further, we validated our method against a few human pathways. The modeling protocol described in this communication can be applied to detect protein-protein interactions in other organisms as well as to construct dimer structures and estimate the confidence of protein interactions experimentally identified with high-throughput techniques

Exact algorithms for pairwise protein structure alignment

Klau, G.W. [Promotor

Characterization and uncertainty analysis of siliciclastic aquifer-fault system

The complex siliciclastic aquifer system underneath the Baton Rouge area, Louisiana, USA, is fluvial in origin. The east-west trending Baton Rouge fault and Denham Springs-Scotlandville fault cut across East Baton Rouge Parish and play an important role in groundwater flow and aquifer salinization. To better understand the salinization underneath Baton Rouge, it is imperative to study the hydrofacies architecture and the groundwater flow field of the Baton Rogue aquifer-fault system. This is done through developing multiple detailed hydrofacies architecture models and multiple groundwater flow models of the aquifer-fault system, representing various uncertain model propositions. The hydrofacies architecture models focus on the Miocene-Pliocene depth interval that consists of the “1,200-foot” sand, “1,500-foot” sand, “1,700-foot” sand and the “2,000-foot” sand, as these aquifer units are classified and named by their approximate depth below ground level. The groundwater flow models focus only on the “2,000-foot” sand. The study reveals the complexity of the Baton Rouge aquifer-fault system where the sand deposition is non-uniform, different sand units are interconnected, the sand unit displacement on the faults is significant, and the spatial distribution of flow pathways through the faults is sporadic. The identified locations of flow pathways through the Baton Rouge fault provide useful information on possible windows for saltwater intrusion from the south. From the results we learn that the “1,200-foot” sand, “1,500-foot” sand and the “1,700-foot” sand should not be modeled separately since they are very well connected near the Baton Rouge fault, while the “2,000-foot” sand between the two faults is a separate unit. Results suggest that at the “2,000-foot” sand the Denham Springs-Scotlandville fault has much lower permeability in comparison to the Baton Rouge fault, and that the Baton Rouge fault plays an important role in the aquifer salinization

Methodologies for the optimisation, control and consideration of uncertainty of reactive distillation

The work presented in this thesis is motivated by the current obstacles hindering the implementation of reactive distillation in industry, mainly related to the complexities of its design and control, as well as the impact of uncertainties thereupon. This work presents a rigorous methodology for the optimal design and control under uncertainty of reactive distillation. The methodology can also be used to identify and investigate mitigation strategies for process failures arising due to design and/or operation deficiencies under changed processing conditions, based on the evaluation of different design and/or control alternatives. The first step of the methodology is the simultaneous (MINLP) optimisation of the design and operation of a reactive distillation process superstructure, used to explore the possible steady-state design alternatives available, including ancillary equipment such as pre- and side-reactors, side-strippers and additional distillation columns, based on product-related constraints and a detailed objective cost function. The next step is the investigation of the dynamic control performance of this optimal system, where conventional and advanced process control strategies are considered in order to investigate how robust the system is towards operational disturbances, or whether revising the optimal steady-state design is required. As the optimisation depends heavily on accurate data for reaction kinetics and separation performance, the final step of the methodology is the evaluation of the impact of parameter uncertainty on the performance of the optimal controlled system, including redesigning the controlled system if required. The methodology is demonstrated using a number of industrially relevant case studies with different reaction and separation characteristics in order to investigate how these determine the design and control of an economically attractive and rigorous reactive distillation process. It is demonstrated that the process characteristics have a significant impact on the design of the system, and that auxiliary equipment may be required to meet production specifications and/or to ensure robust controlled behaviour. It is also shown that, under parameter uncertainty, an optimal controlled system may nevertheless face performance issues, and revising the design and/or operation of the process may be required in order to mitigate such situations

Fiscal Year 2002

The Department of Energy (DOE) and its predecessors have conducted research and development (R&D) in geothermal energy since 1971. To develop the technology needed to harness the Nation's vast geothermal resources, DOE's Office of Geothermal Technologies oversees a network of national laboratories, industrial contractors, universities, and their subcontractors. The goals are: (1) Double the number of States with geothermal electric power facilities to eight by 2006; (2) Reduce the levelized cost of generating geothermal power to 3-5 cents per kWh by 2007; and (3) Supply the electrical power or heat energy needs of 7 million homes and businesses in the United States by 2010. This Federal Geothermal Program Research Update reviews the specific objectives, status, and accomplishments of DOE's Geothermal Program for Federal Fiscal Year (FY) 2002. The information contained in this Research Update illustrates how the mission and goals of the Office of Geothermal Technologies are reflected in each R&D activity. The Geothermal Program, from its guiding principles to the most detailed research activities, is focused on expanding the use of geothermal energy. balanced strategy for the Geothermal Program