Tetranorsesquiterpenoids as Attractants of Yucca Moths to Yucca Flowers

Journal of Chemical Ecology - The obligate pollination mutualism between Yucca and yucca moths is a classical example of coevolution. Oviposition and active pollination by female yucca moths occur...     

Influence of motion correction on the visual analysis of cardiac magnetic resonance stress perfusion imaging

Objective

Image post-processing corrects for cardiac and respiratory motion (MoCo) during cardiovascular magnetic resonance (CMR) stress perfusion. The study analyzed its influence on visual image evaluation.

Materials and methods

Sixty-two patients with (suspected) coronary artery disease underwent a standard CMR stress perfusion exam during free-breathing. Image post-processing was performed without (non-MoCo) and with MoCo (image intensity normalization; motion extraction with iterative non-rigid registration; motion warping with the combined displacement field). Images were evaluated regarding the perfusion pattern (perfusion deficit, dark rim artifact, uncertain signal loss, and normal perfusion), the general image quality (non-diagnostic, imperfect, good, and excellent), and the reader’s subjective confidence to assess the images (not confident, confident, very confident).

Results

Fifty-three (non-MoCo) and 52 (MoCo) myocardial segments were rated as ‘perfusion deficit’, 113 vs. 109 as ‘dark rim artifacts’, 9 vs. 7 as ‘uncertain signal loss’, and 817 vs. 824 as ‘normal’. Agreement between non-MoCo and MoCo was high with no diagnostic difference per-patient. The image quality of MoCo was rated more often as ‘good’ or ‘excellent’ (92 vs. 63%), and the diagnostic confidence more often as “very confident” (71 vs. 45%) compared to non-MoCo.

Conclusions

The comparison of perfusion images acquired during free-breathing and post-processed with and without motion correction demonstrated that both methods led to a consistent evaluation of the perfusion pattern, while the image quality and the reader’s subjective confidence to assess the images were rated more favorably for MoCo.

     

Biofilm Responses to Flow Regulation by Dams in Mediterranean Rivers

Dams regulate downstream hydrology and modify water quality, which in turn can impinge on the biota, especially in rivers naturally subject to large hydrological variability, such as those under Mediterranean climate. The effect of dams on biofilms was analysed in three tributaries (Cinca, Siurana and Montsant) of the Ebro River (NE Spain). We hypothesized that flow regulation would lead to lower spatial variability of biofilms on the streambed and to a decrease in their metabolic rate per unit biomass, especially during low flow periods. Biofilm characteristics were studied in five transects evenly spaced along river reaches upstream (control) and downstream (impact) of dams in each river, along with riverbed granulometry, hydraulics and water chemistry. Chlorophyll‐a, respiratory activity, photosynthetic capacity and efficiency, and extracellular enzymatic activities (β‐d ‐glucosidase, alkaline phosphatase and leucine‐amino‐peptidase) of epilithic biofilms were measured in different seasons. Spatial variability of chemical and biological variables was reduced downstream of the dams. Chlorophyll‐a concentration, photosynthetic efficiency and respiration capacity were higher in impact than in control reaches, but generally, low inorganic phosphorus concentrations resulted in comparable phosphatase activities downstream and upstream of dams. On the other hand, β‐d ‐glucosidase and leucine‐amino‐peptidase activities were higher at impact reaches. Biofilms were thicker and metabolically more active at the impact reaches, with higher ability to transform dissolved organic matter. Overall, results from this study provide evidence that dams can largely affect the structure and activity of river biofilms, with foreseeable important consequences for river ecosystem functioning. Copyright © 2014 John Wiley & Sons, Ltd.     

Automated interpretation and accessible presentation of technical diagrams for blind people

The EU-supported TeDUB (Technical Drawings Understanding for the Blind) project is developing a software system that aims to make technical diagrams accessible to blind and visually impaired people. It consists of two separate modules: one that analyses drawings either semi-automatically or automatically, and one that presents the results of this analysis to blind people and allows them to interact with it. The system is capable of analysing and presenting diagrams from a number of formally defined domains. A diagram enters the system as one of two types: first, diagrams contained in bitmap images, which do not explicitly contain the semantic structure of their content and thus have to be interpreted by the system, and second, diagrams obtained in a semantically enriched format that already yields this structure. The TeDUB system provides blind users with an interface to navigate and annotate these diagrams using a number of input and output devices. Extensive user evaluations have been carried out and an overall positive response from the participants has shown the effectiveness of the approach.     

An improved formalism for quantum computation based on geometric algebra—case study: Grover’s search algorithm

The Grover search algorithm is one of the two key algorithms in the field of quantum computing, and hence it is desirable to represent it in the simplest and most intuitive formalism possible. We show firstly, that Clifford’s geometric algebra, provides a significantly simpler representation than the conventional bra-ket notation, and secondly, that the basis defined by the states of maximum and minimum weight in the Grover search space, allows a simple visualization of the Grover search analogous to the precession of a spin- ${\frac{1}{2}}$ particle. Using this formalism we efficiently solve the exact search problem, as well as easily representing more general search situations. We do not claim the development of an improved algorithm, but show in a tutorial paper that geometric algebra provides extremely compact and elegant expressions with improved clarity for the Grover search algorithm. Being a key algorithm in quantum computing and one of the most studied, it forms an ideal basis for a tutorial on how to elucidate quantum operations in terms of geometric algebra—this is then of interest in extending the applicability of geometric algebra to more complicated problems in fields of quantum computing, quantum decision theory, and quantum information.     

Figure-ground separation by cue integration

This letter presents an improved cue integration approach to reliably separate coherent moving objects from their background scene in video sequences. The proposed method uses a probabilistic framework to unify bottom-up and top-down cues in a parallel, "democratic" fashion. The algorithm makes use of a modified Bayes rule where each pixel's posterior probabilities of figure or ground layer assignment are derived from likelihood models of three bottom-up cues and a prior model provided by a top-down cue. Each cue is treated as independent evidence for figure-ground separation. They compete with and complement each other dynamically by adjusting relative weights from frame to frame according to cue quality measured against the overall integration. At the same time, the likelihood or prior models of individual cues adapt toward the integrated result. These mechanisms enable the system to organize under the influence of visual scene structure without manual intervention. A novel contribution here is the incorporation of a top-down cue. It improves the system's robustness and accuracy and helps handle difficult and ambiguous situations, such as abrupt lighting changes or occlusion among multiple objects. Results on various video sequences are demonstrated and discussed. (Video demos are available at http://organic.usc.edu:8376/ approximately tangx/neco/index.html .).     

Rapid convergence to feature layer correspondences

We describe a neural network able to rapidly establish correspondence between neural feature layers. Each of the network's two layers consists of interconnected cortical columns, and each column consists of inhibitorily coupled subpopulations of excitatory neurons. The dynamics of the system builds on a dynamic model of a single column, which is consistent with recent experimental findings. The network realizes dynamic links between its layers with the help of specialized columns that evaluate similarities between the activity distributions of local feature cell populations, are subject to a topology constraint, and can gate the transfer of feature information between the neural layers. The system can robustly be applied to natural images, and correspondences are found in time intervals estimated to be smaller than 100 ms in physiological terms.     

Empirical evaluation of an educational game on software measurement

Software measurement is considered important in improving the software process. However, teaching software measurement remains a challenging issue. Although, games and simulations are regarded powerful tools for learning, their learning effectiveness is not rigorously established. This paper describes the results of an explorative study to investigate the learning effectiveness of a game prototype on software measurement in order to make an initial judgment about its potential as an educational tool as well as to analyze its appropriateness, engagement and strengths & weaknesses as guidance for further evolution. Within the study, a series of experiments was conducted in parallel in three master courses in Brazil. Results of the study reveal that the participants consider the content and structure of the game appropriate, but no indication for a significant difference on learning effectiveness could be shown.