Fast-changing Systems Research Articles

Ciliates in man-made mountain reservoirs

Climate warming has multiple effects on an environment. Especially the Alpine region is affected by changing conditions, which do not only have ecological but also economic impacts in respect to winter sports tourism. Due to higher environmental temperatures and less precipitation, artificial snow making is becoming increasingly important and consequently, mountain reservoirs for water storage are built. In these systems, planktonic communities are not only influenced by the naturally harsh environmental conditions of the alpine region, but also by severe changes in water level fluctuations due to water withdrawal and re-filling within short time periods. Information on planktonic communities and species traits in such man-made water bodies is nonexistent. Here, we focused on ciliates, a group of unicellular protists known to adapt and respond rapidly to changing environmental conditions. Simultaneously, we identified abiotic and other biotic factors that shaped these microbial communities. We investigated the species composition, abundance and species traits of ciliates in eleven mountain reservoirs in the Tyrolean Alps, Austria, and hypothesized that these communities differed significantly from natural ones. The mountain reservoirs were investigated twice during the ice-free season and water chemistry, chlorophyll a, bacteria, zooplankton, and ciliates were sampled. We detected 48 ciliate taxa in total, with an average of five taxa per mountain reservoir. A wide range of abundance (summer: 24 to >15,600 Ind L−1; autumn: 38 to ∼7,500 Ind L−1) and no clear pattern in the community composition was found, most likely due to water level fluctuations and the source of water used for filling the mountain reservoirs. The ciliate abundance was significantly affected by pH, nutrients, but also water transparency and potential predators (crustaceans). Planktonic ciliates dominated the mountain reservoirs and, surprisingly, mixotrophic species, typically found in natural (alpine) lakes, were only rarely observed. Our data suggest that in these fast-changing systems, local factors seem to be more important than regional ones.

Agile Governance for Complex and Fast-changing Systems

Agile Governance for Complex and Fast-changing Systems

Does not compute: Avoiding pitfalls assessing the Internet's energy and carbon impacts

Does not compute: Avoiding pitfalls assessing the Internet's energy and carbon impacts

Maize fields are a potential sink for an outbreaking mirid bug pest in Chinese Bt-cotton agricultural landscapes

Agricultural landscapes are fast-changing systems due to crop planting and harvesting. These events strongly influence movements of arthropod pests and their natural enemies, yet they are insufficiently considered to implement informed pest management strategies. In China, the adoption of Bt-cotton crops at very large scales has given rise to the recent pest status of mirid bugs such as Apolygus lucorum in cotton fields. In this study we relied on carbon 13 stable isotope analysis to estimate the dispersal of A. lucorum in the Bt-cotton agricultural landscape, composed of a mosaic of cotton and maize and other minor crops. We showed that a diet on C3-plants including cotton induced a significantly different signature than the C4-plant maize. Based on δ13C ratios, we showed that more than 75% of mirid bugs caught in maize fields did not originate in situ, since they had a C3-diet and therefore most likely dispersed from neighbouring cotton fields. Conversely, less than 10% of mirid bugs in cotton fields had a diet on C4-plants, so the vast majority of them did not disperse from maize fields but instead likely stayed in cotton fields. We also observed a delayed establishment of A. lucorum populations in maize fields compared to cotton fields, likely due to host phenology. Indeed we showed in laboratory that juveniles’ survival rate and adults’ fecundity are high on maize silk and grain only, whose resources are available in the field shortly before harvest. Unidirectional movements of mirids from cotton to maize associated with poor developmental success on maize highlight the high potential of maize fields to act as a sink for A. lucorum mirid bug pests. This could be wisely implemented in IPM programs to enhance the management of mirid bug population outbreaks in cotton fields and reduce yield loss on cotton.

Natural Computing Applied to the Underground System: A Synergistic Approach for Smart Cities.

The management and proper use of the Urban Public Transport Systems (UPTS) constitutes a critical field that has not been investigated in accordance to its relevance and urgent idiosyncrasy within the Smart Cities realm. Swarm Intelligence is a very promising paradigm to deal with such complex and dynamic systems. It presents robust, scalable, and self-organized behavior to deal with dynamic and fast changing systems. The intelligence of cities can be modelled as a swarm of digital telecommunication networks (the nerves), ubiquitously embedded intelligence, sensors and tags, and software. In this paper, a new approach based on the use of the Natural Computing paradigm and Collective Computation is shown, more concretely taking advantage of an Ant Colony Optimization algorithm variation and Fireworks algorithms to build a system that makes the complete control of the UPTS a tangible reality.

Fully Parallel Electrical Impedance Tomography Using Code Division Multiplexing.

Electrical Impedance Tomography (EIT) has been dominated by the use of Time Division Multiplexing (TDM) and Frequency Division Multiplexing (FDM) as methods of achieving orthogonal injection of excitation signals. Code Division Multiplexing (CDM), presented in this paper is an alternative that eliminates temporal data inconsistencies of TDM for fast changing systems. Furthermore, this approach eliminates data inconsistencies that arise in FDM when frequency bands of current injecting electrodes are chosen over frequencies that have large changes in the imaged object's impedance. To the authors knowledge no fully functional wideband system or simulation platform using simultaneous injection of Gold codes currents has been reported. In this paper, we formulate, simulate and develop a fully functional pseudo-random (Gold) code driven EIT system with 15 excitation currents and 16 separate voltage measurement electrodes. In the work we verify the use of CDM as a multiplexing modality in simultaneous injection EIT, using a prototype system with an overall bandwidth of 15 kHz, and attainable speed of 462 frames/s using codes with a period of 31 chips. Simulations and experiments are performed using the Electrical Impedance and Diffuse Optics Reconstruction Software (EIDORS). We also propose the use of image processing on reconstructed images to establish their quality quantitatively without access to raw reconstruction data. The results of this study show that CDM can be successfully used in EIT, and gives results of similar visual quality to TDM and FDM. Achieved performance shows average position error of 3.5% and size error of 6.2%.

Comparative study of layered and volumetric rescanning for different scanning speeds of proton beam in liver patients

In recent years, particle therapy has become a widely accepted form of cancer treatment and technological advances in beam delivery technology (i.e. pencil beam scanning (PBS)) have enabled the application of highly conformal dose distributions to static targets. Current research focuses on the possibilities for the treatment of mobile targets with these techniques. Of different motion mitigation methods being investigated, rescanning is perhaps the easiest to apply clinically. In general however, different PBS delivery systems exhibit a different temporal parameter space between delivery and target motions, due to the system specific beam position adjustment times (BPATs). Depending on these BPATs, dosimetric effects appearing during irradiation of moving targets vary significantly. In this work, volumetric and layered rescanning were compared for four different scenarios—a combination of fast and slow BPATs laterally (4 ms and 10 ms) and in depth (80 ms and 1 s); and nine different treatment plan arrangements for two clinical liver cases. 4D dose calculations were performed assuming regular, sinusoidal rigid motion as a worst-case motion scenario to model interplay effects. Calculations were sampled over three different starting phases resulting in a total of 432 dose distributions. It was found that layered rescanning is the method of choice for slow scanning systems, both in terms of dose homogeneity (D5–95 values are lower by up to 16% with layered rescanning) and in the estimated treatment delivery times (reduction of up to 300 s with layered rescanning). Analysis of dose homogeneity showed that layered rescanning leads to a smoother decrease in dose inhomogeneity as a function of the number of rescans than volumetric rescanning, which shows larger fluctuations. However, layered rescanning appears to be more sensitive to the starting phase. When analyzing the performance of both approaches and different scanning speeds as a function of delivery time, layered rescanning appears to be the only viable approach for slow energy changing systems, even approaching the performance of fast energy changing systems, as long as lateral scanning speeds are kept high. Similar results were found for multiple field plans and when analyzing different field directions.

A Relational Approach to Organization Design

The paper criticizes the currently dominant view of organization forms as “discrete alternatives” and “coherent” set attributes, and proposes a more refined and micro‐analytic view of organization forms as particular combinations of coordination mechanisms and rights allocations. This view is relevant for understanding and devising “new” forms and proposing solutions for governing the composite and fast changing systems of today. The view is “relational” as it offers a procedure for devising “superior” configurations as combinations—relations between organizational components—in a quasi‐continuous space of possibilities. The approach is sustained by the quantitative methods of network analysis as applied to relations among firm's resources and activities. Theoretically, the approach revisits organization design, integrating classic organization theory tenets with the new inputs provided by organizational economics. Substantively, it is argued that a mix of much differentiated coordination mechanisms is usually superior to the codified, “packaged”, allegedly “coherent”, forms of organization. The procedure presented in the paper is applied to a field experiment in a medium size firm.1 1. The initial idea of network‐analytic, relational design was originally presented in a paper by the authors at the 1998 EGOS Colloquium, in Maastricht, the Netherlands. A development of the framework was presented as a keynote presentation at the LINK (Learning, Incentives and Knowledge) Project 2000 Annual Conference at Copenhagen Business School. In the present paper, the model of interdependence and coordination has been substantially revised and stylized, leading to formulate a new model of optimal coordination. The case study has been enriched and completed with new data gathering activities in spring 2005.

On-line RBFNN based identification of rapidly time-varying nonlinear systems with optimal structure-adaptation

This paper presents an adaptive RBF network for the on-line identification and tracking of rapidly-changing time-varying nonlinear systems. The proposed algorithm is capable of maintaining the accuracy of learned patterns even when a large number of aged patterns are replaced by new ones through the adaptation process. Moreover, the algorithm exhibits a strong learning capacity with instant embodiment of new data which makes it suitable for tracking of fast-changing systems. However, the accuracy and speed in the adaptation is balanced by the computational cost which increases with the square of the number of the radial basis functions, resulting in a computational expensive, but still practically feasible, algorithm. The simulation results show the effectiveness (in terms of degradation of learned patterns and learning capacity) of this architecture for adaptive modeling.

Fine-Resolution 4DVAR Data Assimilation for the Great Plains Tornado Outbreak of 3 May 1999

Abstract The National Centers for Environmental Prediction fine-resolution four-dimensional variational (4DVAR) data assimilation system is used to study the Great Plains tornado outbreak of 3 May 1999. It was found that the 4DVAR method was able to capture very well the important precursors for the tornadic activity, such as upper- and low-level jet streaks, wind shear, humidity field, surface CAPE, and so on. It was also demonstrated that, in this particular synoptic case, characterized by fast-changing mesoscale systems, the model error adjustment played a substantial role. The experimental results suggest that the common practice of neglecting the model error in data assimilation systems may not be justified in synoptic situations similar to this one.