Method for large-scale isolation and purification of R-phycoerythrin from red alga Polysiphonia urceolata Grev

R-phycoerythrin was isolated and purified from a red alga, Polysiphonia urceolata Grev, using Streamline column combined with ion-exchange chromatography or hydroxyapatite chromatography. The purity of R-phycoerythrin isolated by Streamline column was up to 1.66 and the yield of R-phycoerythrin could be as high as 0.68 mg/g frozen P. urceolata. All the eluates from Streamline column were divided into two equivalent parts, respectively. One part was pumped into the ion-exchange column loaded with Q-Sepharose and the other was applied to the adsorption column loaded with hydroxyapatite. The purities of R-phycoerythrin purified using these two methods were both up to 3.26, more than 3.2 the commonly accepted criterion. The yield of purified R-phycoerythrin from the ion-exchange chromatography was 0.40 mg/g frozen P. urceolata and that from the hydroxyapatite chromatography could reach 0.34 mg/g frozen P. urceolata. The purified protein had three absorption peaks at 498, 535, and 565 nm and displayed a fluorescence maximum at 580 nm, which was consistent with the typical spectrum of R-phycoerythrin. The purified R-PE was also identified with electrophoresis. Only one single protein band appeared on native-PAGE with silver staining. SDS-PAGE demonstrated the presence of one 20 kDa major subunit, and one low intensity band corresponding to 33 kDa subunit. The results indicate that using the expanded bed adsorption combined with ion-exchange chromatography or hydroxyapatite chromatography, R-phycoerythrin can be purified from frozen P. urceolata on large scale. (c) 2006 Elsevier Inc. All rights reserved.

Progress of large-scale air-sea interaction studies in China

This paper summarizes the progress of large-scale air-sea interaction studies that has been achieved in China in the four-year period from July 1998 to July 2002, including seven aspects in the area of the air-sea interaction, namely air-sea interaction related to the tropical Pacific Ocean, monsoon-related air-sea interaction, air-sea interaction in the north Pacific Ocean, air-sea interaction in the Indian Ocean, air-sea interactions in the global oceans, field experiments, and oceanic cruise surveys. However more attention has been paid to the first and the second aspects because a large number of papers in the reference literature for preparing and organizing this paper are concentrated in the tropical Pacific Ocean, such as the ENSO process with its climatic effects and dynamics, and the monsoon-related air-sea interaction. The literature also involves various phenomena with their different time and spatial scales such as intraseasonal, annual, interannual, and interdecadal variabilities in the atmosphere/ocean interaction system, reflecting the contemporary themes in the four-year period at the beginning of an era from the post-TOGA to CLIVAR studies. Apparently, it is a difficult task to summarize the great progress in this area, as it is extracted from a large quantity of literature, although the authors tried very hard.

COASTAL SEA-LEVEL AND THE LARGE-SCALE CLIMATE STATE - A DOWNSCALING EXERCISE FOR THE JAPANESE ISLANDS

A major problem which is envisaged in the course of man-made climate change is sea-level rise. The global aspect of the thermal expansion of the sea water likely is reasonably well simulated by present day climate models; the variation of sea level, due to variations of the regional atmospheric forcing and of the large-scale oceanic circulation, is not adequately simulated by a global climate model because of insufficient spatial resolution. A method to infer the coastal aspects of sea level change is to use a statistical ''downscaling'' strategy: a linear statistical model is built upon a multi-year data set of local sea level data and of large-scale oceanic and/or atmospheric data such as sea-surface temperature or sea-level air-pressure. We apply this idea to sea level along the Japanese coast. The sea level is related to regional and North Pacific sea-surface temperature and sea-level air pressure. Two relevant processes are identified. One process is the local wind set-up of water due to regional low-frequency wind anomalies; the other is a planetary scale atmosphere-ocean interaction which takes place in the eastern North Pacific.

The effect of the causative algae of large-scale HAB in the East China Sea on egg hatching of Argopecten irradians, and population growth of Brachionus plicatilis and Moina mongolica

The impacts of Prorocentrum donghaiense Lu and Alexandrium catenella Balech, causative species of the large-scale HAB in the East China Sea, were studied under laboratory conditions. According to bloom densities, the effects of monoculture and mixture of the two species were examined on the egg-hatching success of Argopecten irradians Lamarck, and the population growth of Brachionus plicatilis Muller and Moina mongolica Daday. The results showed that monoculture of A. catenella had a significant inhibition on the egg hatching success of A. irradians, and the population growth of B. plicatilis and M. mongolica. The median effective densities ( EDSo) inhibiting the egg hatching success of A. irradians for 24 h and the population growth of B. plicatilis and M. mongolica for 96 h were 800, 630, and 2 400 cells/cm(3), respectively. Monoculture of P. donghaiense has no such inhibitory effect on the egg hatching success of A. irradians; P. donghaiense at lower suitable densities could sustain the population growth of B. plicatilis (1 x 10(4) similar to 3 x 10(4)cells/cm(3)) and M. mongolica (2 x 10(4) similar to 5 x 10(4) cells/cm(3)); P. doaghaiense at higher densities had significantly adverse effect on the population growth of B. plicatilis (4 x 10(4) similar to 10 x 10(4) cells/cm(3)) and M. mongolica (10 x 10(4) cells/cm(3)). When the two algae were mixed according to bloom densities, P. donghaiense at suitable densities to some extent could decrease the toxicity of A. catenella to B. plicatilis and M. mongolica. The results indicated that the large-scale HAB in the East China Sea could have adverse effect on zooplankton, and might further influence the marine ecosystem, especially when there was also Alexandrium bloom.

Robust, High-Speed Network Design for Large-Scale Multiprocessing

As multiprocessor system size scales upward, two important aspects of multiprocessor systems will generally get worse rather than better: (1) interprocessor communication latency will increase and (2) the probability that some component in the system will fail will increase. These problems can prevent us from realizing the potential benefits of large-scale multiprocessing. In this report we consider the problem of designing networks which simultaneously minimize communication latency while maximizing fault tolerance. Using a synergy of techniques including connection topologies, routing protocols, signalling techniques, and packaging technologies we assemble integrated, system-level solutions to this network design problem.

Representing Knowledge of Large-Scale Space

This dissertation presents a model of the knowledge a person has about the spatial structure of a large-scale environment: the "cognitive map". The functions of the cognitive map are to assimilate new information about the environment, to represent the current position, and to answer route-finding and relative-position problems. This model (called the TOUR model) analyzes the cognitive map in terms of symbolic descriptions of the environment and operations on those descriptions. Knowledge about a particular environment is represented in terms of route descriptions, a topological network of paths and places, multiple frames of reference for relative positions, dividing boundaries, and a structure of containing regions. The current position is described by the "You Are Here" pointer, which acts as a working memory and a focus of attention. Operations on the cognitive map are performed by inference rules which act to transfer information among different descriptions and the "You Are Here" pointer. The TOUR model shows how the particular descriptions chosen to represent spatial knowledge support assimilation of new information from local observations into the cognitive map, and how the cognitive map solves route-finding and relative-position problems. A central theme of this research is that the states of partial knowledge supported by a representation are responsible for its ability to function with limited information of computational resources. The representations in the TOUR model provide a rich collection of states of partial knowledge, and therefore exhibit flexible, "common-sense" behavior.

An empirical 3D model of the large-scale coronal structure based on the distribution of H? filaments on the solar disk

Morgan, H.; Habbal, S. R., An empirical 3D model of the large-scale coronal structure based on the distribution of H? filaments on the solar disk, Astronomy and Astrophysics, Volume 464, Issue 1, March II 2007, pp.357-365

Generating complex connectivity structures for large-scale neural models

Martin Huelse: Generating complex connectivity structures for large-scale neural models. In: V. Kurkova, R. Neruda, and J. Koutnik (Eds.): ICANN 2008, Part II, LNCS 5164, pp. 849?858, 2008. Sponsorship: EPSRC

Large-scale structure of the fast solar wind

Breen, Andrew; Bisi, M.M.; Fallows, R.A.; Habbal, S.R., (2007) 'Large-scale structure of the fast solar wind', Journal of Geophysical Research 112(A6) pp.A06101 RAE2008

Distributed Placement of Service Facilities in Large-Scale Networks

The effectiveness of service provisioning in largescale networks is highly dependent on the number and location of service facilities deployed at various hosts. The classical, centralized approach to determining the latter would amount to formulating and solving the uncapacitated k-median (UKM) problem (if the requested number of facilities is fixed), or the uncapacitated facility location (UFL) problem (if the number of facilities is also to be optimized). Clearly, such centralized approaches require knowledge of global topological and demand information, and thus do not scale and are not practical for large networks. The key question posed and answered in this paper is the following: "How can we determine in a distributed and scalable manner the number and location of service facilities?" We propose an innovative approach in which topology and demand information is limited to neighborhoods, or balls of small radius around selected facilities, whereas demand information is captured implicitly for the remaining (remote) clients outside these neighborhoods, by mapping them to clients on the edge of the neighborhood; the ball radius regulates the trade-off between scalability and performance. We develop a scalable, distributed approach that answers our key question through an iterative reoptimization of the location and the number of facilities within such balls. We show that even for small values of the radius (1 or 2), our distributed approach achieves performance under various synthetic and real Internet topologies that is comparable to that of optimal, centralized approaches requiring full topology and demand information.

Large-Scale Neural Systems for Vision and Cognition

— Consideration of how people respond to the question What is this? has suggested new problem frontiers for pattern recognition and information fusion, as well as neural systems that embody the cognitive transformation of declarative information into relational knowledge. In contrast to traditional classification methods, which aim to find the single correct label for each exemplar (This is a car), the new approach discovers rules that embody coherent relationships among labels which would otherwise appear contradictory to a learning system (This is a car, that is a vehicle, over there is a sedan). This talk will describe how an individual who experiences exemplars in real time, with each exemplar trained on at most one category label, can autonomously discover a hierarchy of cognitive rules, thereby converting local information into global knowledge. Computational examples are based on the observation that sensors working at different times, locations, and spatial scales, and experts with different goals, languages, and situations, may produce apparently inconsistent image labels, which are reconciled by implicit underlying relationships that the network’s learning process discovers. The ARTMAP information fusion system can, moreover, integrate multiple separate knowledge hierarchies, by fusing independent domains into a unified structure. In the process, the system discovers cross-domain rules, inferring multilevel relationships among groups of output classes, without any supervised labeling of these relationships. In order to self-organize its expert system, the ARTMAP information fusion network features distributed code representations which exploit the model’s intrinsic capacity for one-to-many learning (This is a car and a vehicle and a sedan) as well as many-to-one learning (Each of those vehicles is a car). Fusion system software, testbed datasets, and articles are available from http://cns.bu.edu/techlab.

Development of large-scale colloidal crystallisation methods for the production of photonic crystals

Colloidal photonic crystals have potential light manipulation applications including; fabrication of efficient lasers and LEDs, improved optical sensors and interconnects, and improving photovoltaic efficiencies. One road-block of colloidal selfassembly is their inherent defects; however, they can be manufactured cost effectively into large area films compared to micro-fabrication methods. This thesis investigates production of ‘large-area’ colloidal photonic crystals by sonication, under oil co-crystallization and controlled evaporation, with a view to reducing cracking and other defects. A simple monotonic Stöber particle synthesis method was developed producing silica particles in the range of 80 to 600nm in a single step. An analytical method assesses the quality of surface particle ordering in a semiquantitative manner was developed. Using fast Fourier transform (FFT) spot intensities, a grey scale symmetry area method, has been used to quantify the FFT profiles. Adding ultrasonic vibrations during film formation demonstrated large areas could be assembled rapidly, however film ordering suffered as a result. Under oil cocrystallisation results in the particles being bound together during film formation. While having potential to form large areas, it requires further refinement to be established as a production technique. Achieving high quality photonic crystals bonded with low concentrations (<5%) of polymeric adhesives while maintaining refractive index contrast, proved difficult and degraded the film’s uniformity. A controlled evaporation method, using a mixed solvent suspension, represents the most promising method to produce high quality films over large areas, 75mm x 25mm. During this mixed solvent approach, the film is kept in the wet state longer, thus reducing cracks developing during the drying stage. These films are crack-free up to a critical thickness, and show very large domains, which are visible in low magnification SEM images as Moiré fringe patterns. Higher magnification reveals separation between alternate fringe patterns are domain boundaries between individual crystalline growth fronts.

Anatomical identification of extracellularly recorded cells in large-scale multielectrode recordings.

This study combines for the first time two major approaches to understanding the function and structure of neural circuits: large-scale multielectrode recordings, and confocal imaging of labeled neurons. To achieve this end, we develop a novel approach to the central problem of anatomically identifying recorded cells, based on the electrical image: the spatiotemporal pattern of voltage deflections induced by spikes on a large-scale, high-density multielectrode array. Recordings were performed from identified ganglion cell types in the macaque retina. Anatomical images of cells in the same preparation were obtained using virally transfected fluorescent labeling or by immunolabeling after fixation. The electrical image was then used to locate recorded cell somas, axon initial segments, and axon trajectories, and these signatures were used to identify recorded cells. Comparison of anatomical and physiological measurements permitted visualization and physiological characterization of numerically dominant ganglion cell types with high efficiency in a single preparation.

Exploring the effects of image persistence in low frame rate virtual environments

© 2015 IEEE.In virtual reality applications, there is an aim to provide real time graphics which run at high refresh rates. However, there are many situations in which this is not possible due to simulation or rendering issues. When running at low frame rates, several aspects of the user experience are affected. For example, each frame is displayed for an extended period of time, causing a high persistence image artifact. The effect of this artifact is that movement may lose continuity, and the image jumps from one frame to another. In this paper, we discuss our initial exploration of the effects of high persistence frames caused by low refresh rates and compare it to high frame rates and to a technique we developed to mitigate the effects of low frame rates. In this technique, the low frame rate simulation images are displayed with low persistence by blanking out the display during the extra time such image would be displayed. In order to isolate the visual effects, we constructed a simulator for low and high persistence displays that does not affect input latency. A controlled user study comparing the three conditions for the tasks of 3D selection and navigation was conducted. Results indicate that the low persistence display technique may not negatively impact user experience or performance as compared to the high persistence case. Directions for future work on the use of low persistence displays for low frame rate situations are discussed.

Utilising computational fluid dynamics (CFD) for the modelling of granular material in large-scale engineering processes

In this paper, the framework is described for the modelling of granular material by employing Computational Fluid Dynamics (CFD). This is achieved through the use and implementation in the continuum theory of constitutive relations, which are derived in a granular dynamics framework and parametrise particle interactions that occur at the micro-scale level. The simulation of a process often met in bulk solids handling industrial plants involving granular matter, (i.e. filling of a flat-bottomed bin with a binary material mixture through pneumatic conveying-emptying of the bin in core flow mode-pneumatic conveying of the material coming out of a the bin) is presented. The results of the presented simulation demonstrate the capability of the numerical model to represent successfully key granular processes (i.e. segregation/degradation), the prediction of which is of great importance in the process engineering industry.