Proceedings of the Third Biochemical Engineering Symposium (April 28, 1973)

This report presents the proceedings of the Biochemical Engineering Symposium held at Kansas State University, April 28, 1973. Since a number of the contributions will be published in detail elsewhere, only brief summaries of each contribution are included here. Requests for additional information on projects conducted at The University of Nebraska should be directed to Dr. Peter J. Reilly, and those at Kansas State University to the editors. ContentsKenneth J. Jacobson, Andrew H.C. Chan, and Raymond C. Eliason, "Properties and Utilization of Small Particulates in Cattle Manure" Cady R. Engler and James S. Yohn, "Protein from Manure" Robert J. Williams, "Kinetics of Sucrose Inversion Using Invertase Immobilized on Hollow Fibers of Cellulose Acetate" David F. Aldis and Thomas A. Carlisle, "Study of a Triiodide-Resin Complex Disinfection System" John C. Heydweiller, "Modeling and Analysis of Symbiotic Growth" Kenneth J. Jacobson, "Synchronized Growth of the Blue Green Alga Microcystis aeruginosa" Clarence C. Y. Ron arui Lincoln L. S. Yang, "Computer Modeling of the Reductive Pentose Phosphate Cycle" Ming-ching T. Kuo, "Application of a Parallel Biochemical Oxidation Kinetic Model to the Design of an Activated Sludge System Including a Primary Clarifier" Prakash N. Mishra, "Optimal Synthesis of Water Renovation Systems"

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.

Impact of dams, dam removal and dam-related river engineering structures on sediment connectivity and channel morphology of the Fugnitz and the Kaja Rivers

In terms of changing flow and sediment regimes of rivers, dams are often regarded as the most dominant form of human impact on fluvial systems. Dams can decrease the flux of water and sediments leading to channel changes such as upstream aggradation and downstream degradation. The opposite effects occur when dams are removed. Channel degradation often requires further intervention in terms of river bed and bank protection works. The situation evolves more complex in river systems that are impacted by a series of dams due to feedback processes between the different system compartments. A number of studies have recently investigated geomorphic systems using connectivity approaches to improve the understanding of geomorphic system response to change. This paper presents a case study investigating the impact of dam construction, dam removal and dam-related river bed and bank protection measures on the sediment connectivity and channel morphology of the Fugnitz and the Kaja Rivers using a combination of DEM analyses, field surveys and landscape evolution modelling. For both river systems the results revealed low sediment connectivity accompanied by a fine river bed sediment facies in river sections upstream of active dams and of removed dams with protection measures. Contrarily, high sediment connectivity which was accompanied by a coarse river bed sediment facies was observed in river sections either located downstream of active dams or of removed dams with upstream protection. In terms of channel changes, significant channel degradation was examined at locations downstream of active dams and of removed dams. Channel bed and bank protection measures prevent erosion and channel slope recovery after dam removal. Landscape evolution modeling revealed a complex geomorphic response to dam construction and dam removal as sediment output rates and therefore geomorphic processes have been shown to act in a non-linear manner. These insights are deemed to have major implications for river management and conservation, as quality and state of riverine habitats are determined by channel morphology and river bed sediment composition.

Productive Diversification and Sustainable Use of Complex Social-Ecological Systems: A Comparative Study of Indigenous and Settler Communities in the Bolivian Amazon

Agricultural and forest productive diversification depends on multiple socioeconomic drivers—like knowledge, migration, productive capacity, and market—that shape productive strategies and influence their ecological impacts. Our comparison of indigenous and settlers allows a better understanding of how societies develop different diversification strategies in similar ecological contexts and how the related socioeconomic aspects of diversification are associated with land cover change. Our results suggest that although indigenous people cause less deforestation and diversify more, diversification is not a direct driver of deforestation reduction. A multidimensional approach linking sociocognitive, economic, and ecological patterns of diversification helps explain this contradiction.

Interdisciplinary assessment of complex regional water systems and their future evolution: how socioeconomic drivers can matter more than climate

Modeling of future water systems at the regional scale is a difficult task due to the complexity of current structures (multiple competing water uses, multiple actors, formal and informal rules) both temporally and spatially. Representing this complexity in the modeling process is a challenge that can be addressed by an interdisciplinary and holistic approach. The assessment of the water system of the Crans-Montana-Sierre area (Switzerland) and its evolution until 2050 were tackled by combining glaciological, hydrogeological, and hydrological measurements and modeling with the evaluation of water use through documentary, statistical and interview-based analyses. Four visions of future regional development were co-produced with a group of stakeholders and were then used as a basis for estimating future water demand. The comparison of the available water resource and the water demand at monthly time scale allowed us to conclude that for the four scenarios socioeconomic factors will impact on the future water systems more than climatic factors. An analysis of the sustainability of the current and future water systems based on four visions of regional development allowed us to identify those scenarios that will be more sustainable and that should be adopted by the decision-makers. The results were then presented to the stakeholders through five key messages. The challenges of communicating the results in such a way with stakeholders are discussed at the end of the article.

Decision evaluation in complex risk network systems (DecernsSDSS) demo and Black River case study

The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.

Solving complex problems with a bioinspired model

Membrane systems are parallel and bioinspired systems which simulate membranes behavior when processing information. As a part of unconventional computing, P-systems are proven to be effective in solvingcomplexproblems. A software technique is presented here that obtain good results when dealing with such problems. The rules application phase is studied and updated accordingly to obtain the desired results. Certain rules are candidate to be eliminated which can make the model improving in terms of time.

Engineering an Ontology for Autonomous Systems - The OASys Ontology

This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programe on autonomous systems’ engineering within a model-based control approach. The ontology aims at providing a unified conceptual framework for the autonomous systems’ stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-specific concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous system’s conceptual models. The objective is to obtain and to use these models as main input for the autonomous system’s model-based control system.

Diagnosing Causes of Water Scarcity in Complex Water Resources Systems and Identifying Risk Management Actions

From the water management perspective, water scarcity is an unacceptable risk of facing water shortages to serve water demands in the near future. Water scarcity may be temporary and related to drought conditions or other accidental situation, or may be permanent and due to deeper causes such as excessive demand growth, lack of infrastructure for water storage or transport, or constraints in water management. Diagnosing the causes of water scarcity in complex water resources systems is a precondition to adopt effective drought risk management actions. In this paper we present four indices which have been developed to evaluate water scarcity. We propose a methodology for interpretation of index values that can lead to conclusions about the reliability and vulnerability of systems to water scarcity, as well as to diagnose their possible causes and to propose solutions. The described methodology was applied to the Ebro river basin, identifying existing and expected problems and possible solutions. System diagnostics, based exclusively on the analysis of index values, were compared with the known reality as perceived by system managers, validating the conclusions in all cases

Engineering Agent Systems for Decision Support

This paper discusses how agent technology can be applied to the design of advanced Information Systems for Decision Support. In particular, it describes the different steps and models that are necessary to engineer Decision Support Systems based on a multiagent architecture. The approach is illustrated by a case study in the traffic management domain.

Expert systems for quality prediction in structural engineering

This work deals with quality level prediction in concrete structures through the helpful assistance of an expert system wich is able to apply reasoning to this field of structural engineering. Evidences, hypotheses and factors related to this human knowledge field have been codified into a Knowledge Base in terms of probabilities for the presence of either hypotheses or evidences,and conditional presence of both. Human experts in structural engineering and safety of structures gave their invaluable knowledge and assistance necessary when constructing the "computer knowledge body".

Ontology driven description and engineering of autonomous systems: application to process system engineering

Autonomous systems refer to systems capable of operating in a real world environment without any form of external control for extended periods of time. Autonomy is a desired goal for every system as it improves its performance, safety and profit. Ontologies are a way to conceptualize the knowledge of a specific domain. In this paper an ontology for the description of autonomous systems as well as for its development (engineering) is presented and applied to a process. This ontology is intended to be applied and used to generate final applications following a model driven methodology.

Systems in Engineering Education: account of an experience

Systems Engineering (SE in the following) has not received much attention as a subject matter in engineering curricula. There are several dozens of universities around the world offering programs (most of them at the graduate level) on systems science and engineering. However, SE is, per se, rarely found among the courses offered by engineering schools. This observation does not strictly mean that systems concepts be left apart. For example, it is usual to find specialized courses for systems of some particular classes (e.g., courses on software systems engineering for computing curricula) or for particular phases of the system life cycle (e.g., courses on systems analysis). Even so, these kinds of courses tend to over-emphasize the importance of specific methodologies and, in consequence, to deviate the attention from the realm of systernness

Towards model-driven engineering for mixed-criticality systems: multiPARTES approach

Mixed criticality systems emerges as a suitable solution for dealing with the complexity, performance and costs of future embedded and dependable systems. However, this paradigm adds additional complexity to their development. This paper proposes an approach for dealing with this scenario that relies on hardware virtualization and Model-Driven Engineering (MDE). Hardware virtualization ensures isolation between subsystems with different criticality levels. MDE is intended to bridge the gap between design issues and partitioning concerns. MDE tooling will enhance the functional models by annotating partitioning and extra-functional properties. System partitioning and subsystems allocation will be generated with a high degree of automation. System configuration will be validated for ensuring that the resources assigned to a partition are sufficient for executing the allocated software components and that time requirements are met.

Membrane Systems Working with the PFactor: Best Strategy to Solve Complex Problems.

A membrane system is a massive parallel system, which is inspired by the living cells when processing information. As a part of unconventional computing, membrane systems are proven to be effective in solving complex problems. A new factor is introduced. This factor can decide whether a technique is worthwhile being used or not. The use of this factor provides the best chances for selecting the strategy for the rules application phase. Referring to the “best” is in reference to the one that reduces execution time within the membrane system. A pre-analysis of the membrane system determines the P-factor, which in return advises the optimal strategy to use. In particular, this paper compares the use of two strategies based on the P-factor and provides results upon the application of them. The paper concludes that the P-factor is an effective indicator for choosing the right strategy to implement the rules application phase in membrane systems.