Reporting Leaders and Followers among Trajectories of Moving Point Objects

Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern ‘one object is leading others’, which is based on behavioural patterns discussed in the behavioural ecology literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection, given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms efficiently report leadership patterns.

External power frequency magnetic field-induced jitter on computer monitors

Power frequency magnetic fields with flux densities greater than 0.5 μT are not uncommon in offices. This level has been shown to induce jitter on VDT monitors. In the present project, these magnetic field-induced disturbances have been studied in the laboratory in order to establish a firm technical basis for future studies of the disturbance's influence on eye strain in VDT workers. Eight volunteers judged the occurrence of distortion when an applied external magnetic field was varied both in amplitude and frequency for 8 investigated VDT screens. The level of the external 50 Hz magnetic field when the distortion was detectable ranged from 0.6 to 1.1 μT. If the screen was viewed through a stereomicroscope (25 × magnification), the corresponding level was in the order of 0.2 μT. If the frequency difference between the external magnetic field and the refresh rate of the screen is only ±1-2 Hz, the disturbance is noticeable at even lower flux densities.     

Neutrino oscillation parameter sampling with MonteCUBES

We present MonteCUBES (“Monte Carlo Utility Based Experiment Simulator”), a software package designed to sample the neutrino oscillation parameter space through Markov Chain Monte Carlo algorithms. MonteCUBES makes use of the GLoBES software so that the existing experiment definitions for GLoBES, describing long baseline and reactor experiments, can be used with MonteCUBES. MonteCUBES consists of two main parts: The first is a C library, written as a plug-in for GLoBES, implementing the Markov Chain Monte Carlo algorithm to sample the parameter space. The second part is a user-friendly graphical Matlab interface to easily read, analyze, plot and export the results of the parameter space sampling.

Program summary

Program title: MonteCUBES (Monte Carlo Utility Based Experiment Simulator)Catalogue identifier: AEFJ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFJ_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: GNU General Public LicenceNo. of lines in distributed program, including test data, etc.: 69 634No. of bytes in distributed program, including test data, etc.: 3 980 776Distribution format: tar.gzProgramming language: CComputer: MonteCUBES builds and installs on 32 bit and 64 bit Linux systems where GLoBES is installedOperating system: 32 bit and 64 bit LinuxRAM: Typically a few MBsClassification: 11.1External routines: GLoBES [1,2] and routines/libraries used by GLoBESSubprograms used:Cat Id ADZI_v1_0, Title GLoBES, Reference CPC 177 (2007) 439Nature of problem: Since neutrino masses do not appear in the standard model of particle physics, many models of neutrino masses also induce other types of new physics, which could affect the outcome of neutrino oscillation experiments. In general, these new physics imply high-dimensional parameter spaces that are difficult to explore using classical methods such as multi-dimensional projections and minimizations, such as those used in GLoBES [1,2].Solution method: MonteCUBES is written as a plug-in to the GLoBES software [1,2] and provides the necessary methods to perform Markov Chain Monte Carlo sampling of the parameter space. This allows an efficient sampling of the parameter space and has a complexity which does not grow exponentially with the parameter space dimension. The integration of the MonteCUBES package with the GLoBES software makes sure that the experimental definitions already in use by the community can also be used with MonteCUBES, while also lowering the learning threshold for users who already know GLoBES.Additional comments: A Matlab GUI for interpretation of results is included in the distribution.Running time: The typical running time varies depending on the dimensionality of the parameter space, the complexity of the experiment, and how well the parameter space should be sampled. The running time for our simulations [3] with 15 free parameters at a Neutrino Factory with O(¹⁰⁶) samples varied from a few hours to tens of hours.References:

[1]

P. Huber, M. Lindner, W. Winter, Comput. Phys. Comm. 167 (2005) 195, hep-ph/0407333.

[2]

P. Huber, J. Kopp, M. Lindner, M. Rolinec, W. Winter, Comput. Phys. Comm. 177 (2007) 432, hep-ph/0701187.

[3]

S. Antusch, M. Blennow, E. Fernandez-Martinez, J. Lopez-Pavon, arXiv:0903.3986 [hep-ph].

     

Strategy for Optimizing LC-MS Data Processing in Metabolomics: A Design of Experiments Approach

A strategy for optimizing LC-MS metabolomics data processing is proposed. We applied this strategy on the XCMS open source package written in R on both human and plant biology data. The strategy is a sequential design of experiments (DoE) based on a dilution series from a pooled sample and a measure of correlation between diluted concentrations and integrated peak areas. The reliability index metric, used to define peak quality, simultaneously favors reliable peaks and disfavors unreliable peaks using a weighted ratio between peaks with high and low response linearity. DoE optimization resulted in the case studies in more than 57% improvement in the reliability index compared to the use of the default settings. The proposed strategy can be applied to any other data processing software involving parameters to be tuned, e.g., MZmine 2. It can also be fully automated and used as a module in a complete metabolomics data processing pipeline.     

Nanoscale phase separations in as-fabricated thick super duplex stainless steels

Journal of Materials Science - Nanoscale phase separations, and effects of these, were studied for thick super duplex stainless steel products by atom probe tomography and mechanical testing....     

Does aluminium stimulate the immune system in male rats after oral exposure?

The influence of oral aluminium exposure on the immune system was studied in rats. Male rats were exposed to soluble and labile Al in acidic drinking water (0-500 mg Al/l) for 7-9 weeks. The concentration of Al in femur bone was higher in rats exposed to 50 and 500 mg Al/l (mean concentration 277 and 599 ng Al/g) than in control rats (150 ng Al/g). The Al concentration in blood plasma could only be quantified in the 500 mg/l group (mean 2.7 ng/ml), whereas the concentrations in the control and 50 mg/l groups were low (< 2 ng Al/ml). Exposure of 4-13-weeks-old rats to the highest Al concentration caused an increased number of splenocytes, whereas exposure of 9-16-weeks-old rats to 500 mg Al/l caused an increased number of thymocytes. Moreover, the proliferative response of splenocytes to the mitogen Con A (2 micrograms/ml) was increased by exposure of the 9-16-weeks-old rats to 500 mg Al/l as compared with the controls. The results indicate that oral Al exposure caused a slight stimulation of some immune functions in the rat at Al plasma concentrations normally found in the human population (< 10 ng Al/ml).     

On the use of optimization models for portfolio selection: A review and some computational results

Portfolio theory deals with the question of how to allocate resources among several competing alternatives (stocks, bonds), many of which have an unknown outcome. In this paper we provide an overview of different portfolio models with emphasis on the corresponding optimization problems. For the classical Markowitz mean-variance model we present computational results, applying a dual algorithm for constrained optimization.     

Anwendungspotenzial von Membranprozessen im Konzept der Lignocellulose-Bioraffinerien

The pulp and paper industry is one of the most important industrial sectors worldwide and has a great potential to be a cornerstone for the future bio-economy, in particular lignocellulosic bio-refineries. The potential of the membrane processes in this conversion will be highlighted in three applications related to kraft/sulphate, sulphite and thermomechanical pulping. Furthermore, the challenges of membrane fouling and cleaning with regard to pulping industry will be discussed and an outlook on future developments of membranes in biorefineries will be given.     

Mixing of Acid Rock Drainage with Alkaline Ash Leachates: Formation of Solid Precipitates and pH-Buffering

Three metal-rich, acidic mine waters (from Bersbo and Ljusnarsberg, Sweden) were mixed with alkaline fly ash leachates in various proportions, representing a pH titration. Changes in pH and the loss of metals in solution due to precipitation of solid phases were tracked. Mineral equilibria and changes in pH and alkalinity were simulated using the geochemical code PHREEQC and the MINTEQv4 database, and the measured and simulated pH responses were compared. The formation of solid precipitates corresponded to fairly well-defined pH-buffering regions, reflecting the mine water compositions (notably the levels of Fe, Al, and Mn). Zn precipitation had a distinct buffering effect at near-neutral pH for the mine waters not dominated by iron. The formation of solid Mg phases (carbonate, as well as hydroxide) was indicated at high pH (above 9), but not formation of solid Ca phases, despite high sulfate levels. The phases that precipitated were various amorphous mixtures, mostly of the metals Fe, Al, Mn, Zn, and Mg. For the Fe-rich mine water, pH was poorly simulated with a simple MIX model, while alkalinity predictions agreed reasonably well with measured data. For the Al-rich mine waters, the simulated pH responses agreed well with the measurements. In an additional step, geochemical simulations were performed where selected proxy phases for major elements were forced to precipitate; this significantly improved the pH and alkalinity predictions. This approach may be more efficient than performing mixing experiments and titrations.