Towards a pragmatic approach for dealing with uncertainties in water management practice

Management of water resources is afflicted with uncertainties. Nowadays it is facing more and new uncertainties since pace and dimension of changes (e.g. climatic, demographic) are accelerating and are likely to increase even more in the future. Hence it is crucial to find pragmatic ways to deal with these uncertainties in water management. So far, decision-making under uncertainty in water management is based on either intuition, heuristics and experience of water managers or on expert assessments all of which are only of limited use for water managers in practice. We argue for an analytical yet pragmatic approach to enable practitioners to deal with uncertainties in a more explicit and systematic way and allow for better informed decisions. Our approach is based on the concept of framing, referring to the different ways in which people make sense of the world and of the uncertainties. We applied and tested recently developed parameters that aim to shed light on the framing of uncertainty in two sub-basins of the Rhine. We present and discuss the results of a series of stakeholder interactions in the two basins aimed at developing strategies for improving dealing with uncertainties. The strategies are synthesized in a cross-checking list based on the uncertainty framing parameters as a hands-on tool for systematically identifying improvement options when dealing with uncertainty in water management practice. We conclude with suggestions for testing the developed check-list as a tool for decision aid in water management practice. Key words: water management, future uncertainties, framing of uncertainties, hands-on decision aid, tools for practice, robust strategies, social learnin

Toward a relational concept of uncertainty: about knowing too little, knowing too differently, and accepting not to know

Uncertainty of late has become an increasingly important and controversial topic in water resource management, and natural resources management in general. Diverse managing goals, changing environmental conditions, conflicting interests, and lack of predictability are some of the characteristics that decision makers have to face. This has resulted in the application and development of strategies such as adaptive management, which proposes flexibility and capability to adapt to unknown conditions as a way of dealing with uncertainties. However, this shift in ideas about managing has not always been accompanied by a general shift in the way uncertainties are understood and handled. To improve this situation, we believe it is necessary to recontextualize uncertainty in a broader way¿relative to its role, meaning, and relationship with participants in decision making¿because it is from this understanding that problems and solutions emerge. Under this view, solutions do not exclusively consist of eliminating or reducing uncertainty, but of reframing the problems as such so that they convey a different meaning. To this end, we propose a relational approach to uncertainty analysis. Here, we elaborate on this new conceptualization of uncertainty, and indicate some implications of this view for strategies for dealing with uncertainty in water management. We present an example as an illustration of these concepts. Key words: adaptive management; ambiguity; frames; framing; knowledge relationship; multiple knowledge frames; natural resource management; negotiation; participation; social learning; uncertainty; water managemen

Fuzzy Self-Learning Controllers for Elasticity Management in Dynamic Cloud Architectures

Cloud controllers support the operation and quality management of dynamic cloud architectures by automatically scaling the compute resources to meet performance guarantees and minimize resource costs. Existing cloud controllers often resort to scaling strategies that are codified as a set of architecture adaptation rules. However, for a cloud provider, deployed application architectures are black-boxes, making it difficult at design time to define optimal or pre-emptive adaptation rules. Thus, the burden of taking adaptation decisions often is delegated to the cloud application. We propose the dynamic learning of adaptation rules for deployed application architectures in the cloud. We introduce FQL4KE, a self-learning fuzzy controller that learns and modifies fuzzy rules at runtime. The benefit is that we do not have to rely solely on precise design-time knowledge, which may be difficult to acquire. FQL4KE empowers users to configure cloud controllers by simply adjusting weights representing priorities for architecture quality instead of defining complex rules. FQL4KE has been experimentally validated using the cloud application framework ElasticBench in Azure and OpenStack. The experimental results demonstrate that FQL4KE outperforms both a fuzzy controller without learning and the native Azure auto-scalin

Triple resonant four-wavemixing boosts the yield of continuous coherent VUV generation

Continuous-wave coherent radiation in the vacuum ultraviolet (VUV)wavelength region at 121 nm will be essential for future laser-cooling of trapped antihydrogen [1]. Cold antihydrogen will enable both tests of the fundamental symmetry between matter and antimatter at unprecedented experimental precision [2] and also experiments in antimatter gravity [3]. Another fascinating application of narrowband continuous laser radiation in the VUV is quantum information processing using single trapped ions in Rydberg-states [4, 5]. Here we describe highly efficient continuous four-wave mixing in the VUV by using three different fundamental wavelengths with a sophisticated choice of detunings to resonances of the nonlinear medium. Up to 6 microwatts of vacuum ultraviolet radiation at 121 nm can be generated which corresponds to an increase of three orders of magnitude in efficiency.Comment: 11 pages, 3 figure

Intelligent and adaptive tutoring for active learning and training environments

Active learning facilitated through interactive and adaptive learning environments differs substantially from traditional instructor-oriented, classroom-based teaching. We present a Web-based e-learning environment that integrates knowledge learning and skills training. How these tools are used most effectively is still an open question. We propose knowledge-level interaction and adaptive feedback and guidance as central features. We discuss these features and evaluate the effectiveness of this Web-based environment, focusing on different aspects of learning behaviour and tool usage. Motivation, acceptance of the approach, learning organisation and actual tool usage are aspects of behaviour that require different evaluation techniques to be used

Continuous Lyman-alpha generation by four-wave mixing in mercury for laser-cooling of antihydrogen

Cooling antihydrogen atoms is important for future experiments both to test the fundamental CPT symmetry by high-resolution laser spectroscopy and also to measure the gravitational acceleration of antimatter. Laser-cooling of antihydrogen can be done on the strong 1S-2P transition at the wavelength of Lyman-alpha (121.6nm). A continuous-wave laser at the Lyman-alpha wavelength based on solid-state fundamental lasers is described. By using a two-photon and a near one photon resonance a scan across the whole phasematching curve of the four-wave mixing process is possible. Furthermore the influence of the beam profile of one fundamental beam on the four-wave mixing process is studied.Comment: 4 pages, 4 figure

Big boned: How Fat Storage and other Adaptations Influenced large theropod foraging ecology

Dinosaur foraging ecology has been the subject of scientific interest for decades, yet much of what we understand about it remains hypothetical. We wrote an agent-based model (ABM) to simulate meat energy sources present in dinosaur environments, including carcasses of giant sauropods, along with living, huntable prey. Theropod dinosaurs modeled in this environment (specifically allosauroids, and more particularly, Allosaurus Marsh, 1877) were instantiated with heritable traits favorable to either hunting success or scavenging success. If hunter phenotypes were more reproductively successful, their traits were propagated into the population through their offspring, resulting in predator specialists. If selective pressure favored scavenger phenotypes, the population would evolve to acquire most of their calories from carrion. Data generated from this model strongly suggest that theropods in sauropod-dominated systems evolved to detect carcasses, consume and store large quantities of fat, and dominate carcass sites. Broadly speaking, selective forces did not favor predatory adaptations, because sauropod carrion resource pools, as we modeled them, were too profitable for prey-based resource pools to be significant. This is the first research to test selective pressure patterns in dinosaurs, and the first to estimate theropod mass based on metabolic constraints

Charm-quark mass from weighted finite energy QCD sum rules

The running charm-quark mass in the $\bar{MS}$ scheme is determined from weighted finite energy QCD sum rules (FESR) involving the vector current correlator. Only the short distance expansion of this correlator is used, together with integration kernels (weights) involving positive powers of $s$, the squared energy. The optimal kernels are found to be a simple {\it pinched} kernel, and polynomials of the Legendre type. The former kernel reduces potential duality violations near the real axis in the complex s-plane, and the latter allows to extend the analysis to energy regions beyond the end point of the data. These kernels, together with the high energy expansion of the correlator, weigh the experimental and theoretical information differently from e.g. inverse moments FESR. Current, state of the art results for the vector correlator up to four-loop order in perturbative QCD are used in the FESR, together with the latest experimental data. The integration in the complex s-plane is performed using three different methods, fixed order perturbation theory (FOPT), contour improved perturbation theory (CIPT), and a fixed renormalization scale $\mu$ (FMUPT). The final result is $\bar{m}_c (3\, {GeV}) = 1008\,\pm\, 26\, {MeV}$, in a wide region of stability against changes in the integration radius $s_0$ in the complex s-plane.Comment: A short discussion on convergence issues has been added at the end of the pape

Study of moments of event shapes in e+e- annihilation using JADE data

Data from e+e- annihilation into hadrons collected by the JADE experiment at centre-of-mass energies between 14 GeV and 44 GeV were used to study moments of event shape distributions. The data were compared with Monte Carlo models and with predictions from QCD NLO order calculations. The strong coupling constant measured from the moments is alpha_S(M_Z) = 0.1286 +/- 0.0007 (stat) +/- 0.0011 (expt) +/- 0.0022 (had) +/- 0.0068 (theo), alpha_S(M_Z) = 0.1286 +/- 0.0072 (total error), consistent with the world average. However, systematic deficiencies in the QCD NLO order predictions are visible for some of the higher moments.Comment: JADE note 147 submitted as contributed paper to ICHEP 2004, corrected statistical error of 6 observable average and several typo

Measurement of the Strong Coupling Constant alpha_S from the Four-Jet Rate in e+e- Annihilation using JADE data

Data from e+e- annihilation into hadrons collected by the JADE experiment at centre-of-mass energies between 14 GeV and 44 GeV were used to study the four-jet rate as a function of the Durham algorithm's resolution parameter y_cut. The four-jet rate was compared to a QCD NLO order calculations including NLLA resummation of large logarithms. The strong coupling constant measured from the four-jet rate is alpha_S(M_Z) = 0.1169 +/- 0.0004 (stat) +/- 0.0012 (expt) +/- 0.0021 (had) +/- 0.0007 (theo), alpha_S(M_Z) = 0.1169 +/- 0.0026 (total error) in agreement with the world average.Comment: JADE note 146 submitted as contributed paper to ICHEP 200