Structures and allelopathic effects ofNuphar alkaloids: Nupharolutine and 6,6′-dihydroxythiobinupharidine

Two of the majorNuphar alkaloids, nupharolutine and 6,6-dihydroxythiobinupharidine, were isolated from the aquatic perennial herbNuphar lutea (L.) Sibth. & Sm., yellow water lily. In a lettuce seedling bioassay of the two pure compounds, the former was inactive and the latter was highly inhibitory of radicle elongation at concentrations greater than 2 ppm. Structures and stereochemistry of the two compounds were confirmed by DEPT,¹H-¹H COSY,¹H-¹³C COSY, and¹H-¹H NOESY experiments.     

Role of anionic and nonionic surfactants on the control of particle size and latex colloidal stability in the seeded emulsion polymerization of butyl methacrylate

The evolution of the main colloidal parameters in the seeded starved‐feed semi‐continuous emulsion polymerization of butyl methacrylate (BMA) was investigated, with the main purpose of assessing the effectiveness of the semi‐empirical relationship S = K · S_S · ΔA/A_S as a tool to define the surfactant/monomer feed ratio (∝ K) best suited to achieve a target particle size. In particular, the effect of the type and amount of surfactant [i.e., anionic, sodium dodecyl sulfate (SDS), or nonionic, Brij 58P] added during the semi‐continuous stage was considered. Coagulum formation was never observed under the adopted experimental conditions. To detect the occurrence of secondary nucleation or particle aggregation, or both, the particle size and number of particles, the surface tension and the particle surface coverage ratio were correlated. The best results were obtained with SDS and 0.8 ≤ K ≤ 3. In fact, under the selected experimental conditions, only with SDS did the number of particles remain nearly constant throughout the polymerization at the value defined by the seed latex; the particle size distribution was highly monodisperse, and the final particle diameter closely matched the calculated one (～ 120 nm). The above semi‐empirical relationship based on the adjustable parameter K was validated by running test polymerizations aimed at lattices with well‐defined particle size. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 3083–3094, 2006     

With a little help from my friends

In this paper, we propose a content-based method the for semi-automatic organization of photo albums based on the analysis of how different users organize their own pictures. The goal is to help the user in dividing his pictures into groups characterized by a similar semantic content. The method is semi-automatic: the user starts to assign labels to the pictures and unlabeled pictures are tagged with proposed labels. The user can accept the recommendation or made a correction. To formulate the suggestions is exploited the knowledge encoded in how other users have partitioned their images. The method is conceptually articulated in two parts. First, we use a suitable feature representation of the images to model the different classes that the users have collected, second, we look for correspondences between the criteria used by the different users. Boosting is used to integrate the information provided by the analysis of multiple users. A quantitative evaluation of the proposed approach is obtained by simulating the amount of user interaction needed to annotate the albums of a set of members of the flickr^® photo-sharing community.     

Fully aliphatic polyimides from adamantane‐based diamines for enhanced thermal stability,solubility, transparency,and low dielectric constant

We have synthesized a series of fully aliphatic polyimides (APIs) from bicyclo[2,2,2]oct‐7‐ene‐2,3,5,6‐tetracarboxylic dianhydride (BOCA) and various aliphatic diamines, including linear aliphatic, flexible alicyclic, and rigid adamantyl diamines. We performed the polymerization reactions using one‐step syntheses in m‐cresol at elevated temperatures without the isolation of poly(amic) acid. The chemical composition and structure of the polymers were characterized by nuclear magnetic resonance (NMR) and infrared (IR) spectrometry. The characterization data are reported from analyses using gel permeation chromatography (GPC), thermogravimetric analysis (TGA), differential scanning calorimeter (DSC), and wide‐angle X‐ray diffraction (WXAD) measurements. The polyimides are also subjected to solubility, solution viscosity, tensile strength, transparency, and dielectric constant measurements. The resultant polyimides possess well‐controlled molecular weight, reasonable intrinsic viscosity, good transparency, enhanced solubility, low dielectric constants, and high glass transition temperature, together with marginal thermal and mechanical stability. These properties were enhanced in copolyimides containing equimolar amounts of rigid and flexible moieties. These rigid‐rod APIs derived from the alicyclic dianhydride and aliphatic diamines are promising candidates as advanced materials for future applications in micro‐ and photoelectronic devices. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 3316–3326, 2006     

Upcycling of polypropylene with various concentrations of peroxydicarbonate and dilauroyl peroxide and two processing steps

The influence of two peroxides (peroxydicarbonate/dilauroyl peroxide) with various concentrations (10–200 mmol/kg PP) and their effective opportunity to introduce long chain branched (LCB) were investigated. The dependence of a single and double extrusion step and the changes of the properties were studied. Experiments were carried out in a single screw extruder at 180°C for the first extrusion step (modification) and at 240°C for the second extrusion step (processing simulation). Melt flow rate and dynamic rheological properties were studied at a measuring temperature of 230°C. For the definitive determination of long chain branched polypropylene (LCB-PP) served the extensional rheology measurements. The mechanical properties were examined via tensile test and impact tensile test. Summarized, LCB (melt strength) could be observed via extensional rheology for all modified specimens and the mechanical properties were maintained or even improved for the modified samples. Particularly, samples containing dilauroyl peroxide display excellent mechanical properties in this study.     

When simulated environments make the difference: the effectiveness of different types of training of car service procedures

An empirical analysis was performed to compare the effectiveness of different approaches to training a set of procedural skills to a sample of novice trainees. Sixty-five participants were randomly assigned to one of the following three training groups: (1) learning-by-doing in a 3D desktop virtual environment, (2) learning-by-observing a video (show-and-tell) explanation of the procedures, and (3) trial-and-error. In each group, participants were trained on two car service procedures. Participants were recalled to perform a procedure either 2 or 4 weeks after the training. The results showed that: (1) participants trained through the virtual approach of learning-by-doing performed both procedures significantly better (i.e. p < .05 in terms of errors and time) than people of non-virtual groups, (2) the virtual training group, after a period of non-use, were more effective than non-virtual training (i.e. p < .05) in their ability to recover their skills, (3) after a (simulated) long period from the training—i.e. up to 12 weeks—people who experienced 3D environments consistently performed better than people who received other kinds of training. The results also suggested that independently from the training group, trainees’ visuospatial abilities were a predictor of performance, at least for the complex service procedure, adj R ² = .460, and that post-training performances of people trained through virtual learning-by-doing are not affected by learning styles. Finally, a strong relationship (p < .001, R ² = .441) was identified between usability and trust in the use of the virtual training tool—i.e. the more the system was perceived as usable, the more it was perceived as trustable to acquire the competences.     

A Review of Element-Based Galerkin Methods for Numerical Weather Prediction: Finite Elements,Spectral Elements,and Discontinuous Galerkin

Numerical weather prediction (NWP) is in a period of transition. As resolutions increase, global models are moving towards fully nonhydrostatic dynamical cores, with the local and global models using the same governing equations; therefore we have reached a point where it will be necessary to use a single model for both applications. The new dynamical cores at the heart of these unified models are designed to scale efficiently on clusters with hundreds of thousands or even millions of CPU cores and GPUs. Operational and research NWP codes currently use a wide range of numerical methods: finite differences, spectral transform, finite volumes and, increasingly, finite/spectral elements and discontinuous Galerkin, which constitute element-based Galerkin (EBG) methods. Due to their important role in this transition, will EBGs be the dominant power behind NWP in the next 10 years, or will they just be one of many methods to choose from? One decade after the review of numerical methods for atmospheric modeling by Steppeler et al. (Meteorol Atmos Phys 82:287–301, 2003), this review discusses EBG methods as a viable numerical approach for the next-generation NWP models. One well-known weakness of EBG methods is the generation of unphysical oscillations in advection-dominated flows; special attention is hence devoted to dissipation-based stabilization methods. Since EBGs are geometrically flexible and allow both conforming and non-conforming meshes, as well as grid adaptivity, this review is concluded with a short overview of how mesh generation and dynamic mesh refinement are becoming as important for atmospheric modeling as they have been for engineering applications for many years.     

METIS-II: low resource machine translation

METIS-II was an EU-FET MT project running from October 2004 to September 2007, which aimed at translating free text input without resorting to parallel corpora. The idea was to use “basic” linguistic tools and representations and to link them with patterns and statistics from the monolingual target-language corpus. The METIS-II project has four partners, translating from their “home” languages Greek, Dutch, German, and Spanish into English. The paper outlines the basic ideas of the project, their implementation, the resources used, and the results obtained. It also gives examples of how METIS-II has continued beyond its lifetime and the original scope of the project. On the basis of the results and experiences obtained, we believe that the approach is promising and offers the potential for development in various directions.     

Prediction-based methods for teleoperation across delayed networks

The remote nature of telepresence scenarios can be seen as a strongpoint and also as a weakness. Although it enables the remote control of robots in dangerous or inaccessible environments, it necessarily involves some kind of communication mechanism for the transmission of control signals. This communication mechanism necessarily involves adverse network effects such as delay. Three mechanisms aimed at improving the effects of network delay are presented in this paper: (1) Motion prediction to partially compensate for network delays, (2) force prediction to learn a local force model, thereby reducing dependency on delayed force signals, and (3) haptic data compression to reduce the required bandwidth of high frequency data. The utilized motion prediction scheme was shown to improve operator performance, but had no influence on operator immersion. The force prediction provided haptic feedback through synchronous forces from the local model, thereby stabilizing the control loop. The developed haptic data compression scheme reduced the number of packets sent across the network by 90%, while improving the quality of the haptic feedback.     

On vector averaging over the unit hypersphere

Sample averaging is a commonly used way to smooth out irregularities of data and to get rid of random fluctuations in measurements analysis. In adaptive signal processing, where an adaptive system learns its own parameters in order to perform a predefined task, the learnt parameters-pattern may depend on the initial learning state and on the fluctuations of the statistical features of the input signals to the system. In adaptive system learning, averaging may be employed as a method to merge several learnt parameters-patterns in order to get a better representative pattern. Even in the case of scalar parameters, the concept of averaging is not uniquely defined as scalar parameters spaces may exhibit a rich structure to be dealt with. The case of multiple parameter patterns where single parameters are mutually constrained to each other may exhibit an even richer structure. In the present paper, we deal with the case of parameters-patterns belonging to the unit hypersphere and develop an averaging technique based on the differential geometrical structure of such a curved space. Numerical experiments illustrate the behavior of the developed averaging algorithm.