Copper and human health: biochemistry, genetics, and strategies for modeling dose-response relationships

Copper (Cu) and its alloys are used extensively in domestic and industrial applications. Cu is also an essential element in mammalian nutrition. Since both copper deficiency and copper excess produce adverse health effects, the dose-response curve is U-shaped, although the precise form has not yet been well characterized. Many animal and human studies were conducted on copper to provide a rich database from which data suitable for modeling the dose-response relationship for copper may be extracted. Possible dose-response modeling strategies are considered in this review, including those based on the benchmark dose and categorical regression. The usefulness of biologically based dose-response modeling techniques in understanding copper toxicity was difficult to assess at this time since the mechanisms underlying copper-induced toxicity have yet to be fully elucidated. A dose-response modeling strategy for copper toxicity was proposed associated with both deficiency and excess. This modeling strategy was applied to multiple studies of copper-induced toxicity, standardized with respect to severity of adverse health outcomes and selected on the basis of criteria reflecting the quality and relevance of individual studies. The use of a comprehensive database on copper-induced toxicity is essential for dose-response modeling since there is insufficient information in any single study to adequately characterize copper dose-response relationships. The dose-response modeling strategy envisioned here is designed to determine whether the existing toxicity data for copper excess or deficiency may be effectively utilized in defining the limits of the homeostatic range in humans and other species. By considering alternative techniques for determining a point of departure and low-dose extrapolation (including categorical regression, the benchmark dose, and identification of observed no-effect levels) this strategy will identify which techniques are most suitable for this purpose. This analysis also serves to identify areas in which additional data are needed to better define the characteristics of dose-response relationships for copper-induced toxicity in relation to excess or deficiency.

Flame Synthesis of Complex Fluoride-Based Nanoparticles as Upconversion Phosphors

Recent improvements in precursor chemistry, reactor geometry and run conditions extend the manufacturing capability of traditional flame aerosol synthesis of oxide nanoparticles to metals, alloys and inorganic complex salts. As an example of a demanding composition, we demonstrate here the one-step flame synthesis of nanoparticles of a 4-element non-oxide phosphor for upconversion applications. The phosphors are characterized in terms of emission capability, phase purity and thermal phase evolution. The preparation of flame-made beta-NaYF4 with dopants of Yb, Tm or Yb, Er furthermore illustrates the now available nanoparticle synthesis tool boxes based on modified flamespray synthesis from our laboratories at ETH Zurich. Since scaling concepts for flame synthesis, including large-scale filtration and powder handling, have become available commercially, the development of industrial applications of complex nanoparticles of metals, alloys or most other thermally stable, inorganic compounds can now be considered a feasible alternative to traditional top-down manufacturing or liquid-intense wet chemistry.

Integration of WSNs into enterprise systems based on semantic physical business entities

Internet of Things based systems are anticipated to gain widespread use in industrial applications. Standardization efforts, like 6L0WPAN and the Constrained Application Protocol (CoAP) have made the integration of wireless sensor nodes possible using Internet technology and web-like access to data (RESTful service access). While there are still some open issues, the interoperability problem in the lower layers can now be considered solved from an enterprise software vendors' point of view. One possible next step towards integration of real-world objects into enterprise systems and solving the corresponding interoperability problems at higher levels is to use semantic web technologies. We introduce an abstraction of real-world objects, called Semantic Physical Business Entities (SPBE), using Linked Data principles. We show that this abstraction nicely fits into enterprise systems, as SPBEs allow a business object centric view on real-world objects, instead of a pure device centric view. The interdependencies between how currently services in an enterprise system are used and how this can be done in a semantic real-world aware enterprise system are outlined, arguing for the need of semantic services and semantic knowledge repositories. We introduce a lightweight query language, which we use to perform a quantitative analysis of our approach to demonstrate its feasibility.

On an Application of Microsoft Excel’s Evolutionary Solver to the Resource-Constrained Project Scheduling Problem RCPSP

The Solver Add-in of Microsoft Excel is widely used in courses on Operations Research and in industrial applications. Since the 2010 version of Microsoft Excel, the Solver Add-in comprises a so-called evolutionary solver. We analyze how this metaheuristic can be applied to the resource-constrained project scheduling problem (RCPSP). We present an implementation of a schedule-generation scheme in a spreadsheet, which combined with the evolutionary solver can be used for devising good feasible schedules. Our computational results indicate that using this approach, non-trivial instances of the RCPSP can be (approximately) solved to optimality.

Query Technologies and Applications for Program Comprehension

Industrial software systems are large and complex, both in terms of the software entities and their relationships. Consequently, understanding how a software system works requires the ability to pose queries over the design-level entities of the system. Traditionally, this task has been supported by simple tools (e.g., grep) combined with the programmer's intuition and experience. Recently, however, specialized code query technologies have matured to the point where they can be used in industrial situations, providing more intelligent, timely, and efficient responses to developer queries. This working session aims to explore the state of the art in code query technologies, and discover new ways in which these technologies may be useful in program comprehension. The session brings together researchers and practitioners. We survey existing techniques and applications, trying to understand the strengths and weaknesses of the various approaches, and sketch out new frontiers that hold promise.

Efficient Deployment of Mobile Detectors for Security Applications

We present a real-world problem that arises in security threat detection applications. The problem consists of deploying mobile detectors on moving units that follow predefined routes. Examples of such units are buses, coaches, and trolleys. Due to a limited budget not all available units can be equipped with a detector. The goal is to equip a subset of units such that the utility of the resulting coverage is maximized. Existing methods for detector deployment are designed to place detectors in fixed locations and are therefore not applicable to the problem considered here. We formulate the planning problem as a binary linear program and present a coverage heuristic for generating effective deployments in short CPU time. The heuristic has theoretical performance guarantees for important special cases of the problem. The effectiveness of the coverage heuristic is demonstrated in a computational analysis based on 28 instances that we derived from real-world data.