The allelopathic mechanisms of dominance in bracken (Pteridium aquilinum) in Southern California

Bracken,Pteridium aquilinum, exerts a strong dominance over associated plants throughout much of its worldwide range. Associated plants are often severely inhibited or even excluded from dense stands of the fern. This study investigated the various aspects of herb suppression in bracken stands and assessed the contribution of the various forms of interference between plants to the establishment and maintenance of bracken dominance. It was shown that competition for soil moisture, light, and nutrients could not account for the lack of herbs in bracken stands. Further, uniformity of soil pH, texture, water-holding capacity, and organic matter content ruled out variability in physical factors as a cause. Baiting and trapping experiments showed that the higher concentration of animal activity inside the bracken stands contributed significantly to the pattern of herb suppression, but only against select species. The maintenance of this pattern in the animal-free Santa Cruz Island stands indicates the importance of another factor, allelopathy. It was found that phytotoxins leached from the dead, standing bracken fronds with the first few rains of the wet season were largely responsible for herb suppression. These toxins were isolated in raindrip and from soil inside the fern stands. Removal of the fronds from the stand before the rains could leach them resulted in reinvasion by the herbs after several seasons, and, conversely, placing fronds over the herbs in the grassland brought about herb inhibition. A number of known allelopathic chemicals were tentatively identified from bracken leachates. The importance of the interaction of allelopathy with other factors of plant interference is illustrated by bracken.     

Monitoring the cure of a composite matrix resin with microdielectrometry

This paper presents a study of the cure of glass and graphite fiber epoxy composites using dielectric monitoring techniques. Initial results reported here deal with the neat resin and the relationship between its conductivity and corresponding changes in glass transition temperature during cure.     

Scalable digital hardware for a trapped ion quantum computer

Quantum Information Processing - Many of the challenges of scaling quantum computer hardware lie at the interface between the qubits and the classical control signals used to manipulate them....     

Approximate dynamic programming via iterated Bellman inequalities

In this paper, we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based on solving linear or semidefinite programs, and produces both a bound on the optimal objective, as well as a suboptimal policy that appears to works very well. These results extend and improve bounds obtained in a previous paper using a single Bellman inequality condition. We describe the methods in a general setting and show how they can be applied in specific cases including the finite state case, constrained linear quadratic control, switched affine control, and multi‐period portfolio investment. Copyright © 2014 John Wiley & Sons, Ltd.     

GPU-OSDDA: a bit-vector GPU-based deadlock detection algorithm for single-unit resource systems

This article presents a GPU-based single-unit deadlock detection methodology and its algorithm, GPU-OSDDA. Our GPU-based design utilizes parallel hardware of GPU to perform computations and thus is able to overcome the major limitation of prior hardware-based approaches by having the capability of handling thousands of processes and resources, whilst achieving real-world run-times. By utilizing a bit-vector technique for storing algorithm matrices and designing novel, efficient algorithmic methods, we not only reduce memory usage dramatically but also achieve two orders of magnitude speedup over CPU equivalents. Additionally, GPU-OSDDA acts as an interactive service to the CPU, because all of the aforementioned computations and matrix management techniques take place on the GPU, requiring minimal interaction with the CPU. GPU-OSDDA is implemented on three GPU cards: Tesla C2050, Tesla K20c, and Titan X. Our design shows overall speedups of 6-595X over CPU equivalents.     

Map‐based Visualizations Increase Recall Accuracy of Data

We investigate the memorability of data represented in two different visualization designs. In contrast to recent studies that examine which types of visual information make visualizations memorable, we examine the effect of different visualizations on time and accuracy of recall of the displayed data, minutes and days after interaction with the visualizations. In particular, we describe the results of an evaluation comparing the memorability of two different visualizations of the same relational data: node‐link diagrams and map‐based visualization. We find significant differences in the accuracy of the tasks performed, and these differences persist days after the original exposure to the visualizations. Specifically, participants in the study recalled the data better when exposed to map‐based visualizations as opposed to node‐link diagrams. We discuss the scope of the study and its limitations, possible implications, and future directions.     

Involving the user Through Library 2.0

Libraries, as we know them today, can be defined by the term Library 1.0. This defines the way resources are kept on shelves or at a computer behind a login. These resources can be taken from a shelf, checked out by the library staff, taken home for a certain length of time and absorbed, and then returned to the library for someone else to avail of. Library 1.0 is a one-directional service that takes people to the information they require. Library 2.0 – or L2 as it is now more commonly addressed as – aims to take the information to the people by bringing the library service to the Internet and getting the users more involved by encouraging feedback participation. This paper presents an overview of Library 2.0 and introduces web 2.0 concepts.     

QuickBird and Hyperion data analysis of an invasive plant species in the Galapagos Islands of Ecuador: Implications for control and land use management

In the Galapagos Islands of Ecuador, one of the greatest threats to the terrestrial ecosystem is the increasing number and areal extent of invasive species. Increased human presence on the islands has hastened the introduction of plant and animal species that threaten the native and endemic flora and fauna. Considerable research on invasive species in the Galapagos Islands has been conducted by the Charles Darwin Foundation. We complement that work through a spatially- and spectrally-explicit satellite assessment of an important invasive plant species (Psidium guajava — guava) on Isabela Island that integrates diverse remote sensing systems, data types, spatial and spectral resolutions, and analytical and image processing approaches. QuickBird and Hyperion satellite data are processed to characterize the areal extent and spatial structure of guava through the following approaches: (1) QuickBird data are classified through a traditional pixel-based approach (i.e., an unsupervised classification approach using the ISODATA algorithm), as well as an Object-Based Image Analysis (OBIA) approach; (2) multiple approaches for spectral “unmixing” of the Hyperion hyper-spectral data are assessed to construct spectral end-members from QuickBird data using linear and non-linear mixture modeling approaches; and (3) landscape pattern metrics are calculated and compared for the pixel-based, object-based, and spectral unmixing approaches. The spectral–spatial characteristics of guava are interpreted relative to management strategies for the control of guava and the restoration of natural ecosystems in the Galapagos National Park.     

Wetland change mapping for the U.S. mid-Atlantic region using an outlier detection technique

Although the impacts of wetland loss are often felt at regional scales, effective planning and management require a comparative assessment of local needs, costs, and benefits. Satellite remote sensing can provide spatially explicit, synoptic land cover change information to support such an assessment. However, a common challenge in conventional remote sensing change detection is the difficulty of obtaining phenologically and radiometrically comparable data from the start and end of the time period of interest. An alternative approach is to use a prior land cover classification as a surrogate for historic satellite data and to examine the self-consistency of class spectral reflectances in recent imagery. We produced a 30-meter resolution wetland change probability map for the U.S. mid-Atlantic region by applying an outlier detection technique to a base classification provided by the National Wetlands Inventory (NWI). Outlier-resistant measures – the median and median absolute deviation – were used to represent spectral reflectance characteristics of wetland class populations, and formed the basis for the calculation of a pixel change likelihood index. The individual scene index values were merged into a consistent region-wide map and converted to pixel change probability using a logistic regression calibrated through interpretation of historic and recent aerial photography. The accuracy of a regional change/no-change map produced from the change probabilities was estimated at 89.6%, with a Kappa of 0.779. The change probabilities identify areas for closer inspection of change cause, impact, and mitigation potential. With additional work to resolve confusion resulting from natural spatial heterogeneity and variations in land use, automated updating of NWI maps and estimates of areal rates of wetland change may be possible. We also discuss extensions of the technique to address specific applications such as monitoring marsh degradation due to sea level rise and mapping of invasive species.