Asymmetric Synthesis with N‐Heterocyclic Carbenes. Application to the Copper‐Catalyzed Conjugate Addition

Chiral N‐heterocyclic carbenes are good ligands for the copper‐catalyzed conjugate addition of dialkylzinc reagents to various Michael acceptors. With as little as 4% of chiral ligand, the enantioselectivity may reach 93% on cycloheptenone.     

Large‐scale anaerobic degradation of betaine

Betaine, also known as N,N,N‐trimethyl glycine, is a soluble nitrogenous compound present at significant concentrations in sugar‐beet molasses. Molasses is used as substrate in a wide range of industrial fermentations, for example, alcohol, acid and yeast cell production. Betaine is not consumed to any significant extent during these fermentations and appears to largely pass through the subsequent processing stages, becoming an important constituent of the wastewater produced by these industries. The present study confirmed that betaine is present in large amounts in sugar‐beet molasses (up to 6% w/w) and in the effluent of processes using sugar‐beet molasses as substrate (up to 4.5 g dm⁻³). Betaine appeared to be almost completely degraded in the two full‐scale anaerobic treatment plants sampled. This was confirmed by anaerobic activity tests performed with both acclimated and unacclimated anaerobic sludge. The results obtained suggest the possible involvement of a multistep degradation process, with the likelihood of a nitrogen‐containing intermediate. Finally, although not totally discountable, betaine degradation does not appear to be coupled to sulfate reduction during treatment of high‐sulfate wastewaters. © 1999 Society of Chemical Industry     

Establishment of a knee-joint coordinate system from helical axes analysis--a kinematic approach without anatomical referencing

This study establishes a functional knee-joint coordinate system (FCS) derived from active motion. The scale invariant properties of helical axes were used in order to avoid inter-observer errors associated with the traditional anatomical referencing techniques. The algorithm was tested with six cadaveric specimens in a knee-joint motion and loading apparatus. To determine the FCS sensitivity to variable loading, rotational moments were applied to the tibia while extending and flexing the knee. Each derived FCS was compared with the clinically derived anatomical coordinate system (ACS). The FCS was reproducible when the loading condition was the same. Changing the rotational moments from internal to external affected the orientations and the positions of the FCS. The largest displacement of 20.8 mm in average occurred in the medio/lateral direction. The FCS corresponded with the ACS for all specimens and loading conditions. The origin was always located within the femur along the transepicondylar line. The orientations differed less than 16.6 degrees in average, thus allowing the use of clinical terminology. These findings suggest that the FCS might improve the ability to clinically assess kinematic alterations provided that the reference motion is reproducible.     

FeO0.7F1.3/C Nanocomposite as a High‐Capacity Cathode Material for Sodium‐Ion Batteries

Searching high capacity cathode materials is one of the most important fields of the research and development of sodium‐ion batteries (SIBs). Here, we report a FeO_0.7F_1.3/C nanocomposite synthesized via a solution process as a new cathode material for SIBs. This material exhibits a high initial discharge capacity of 496 mAh g^?1 in a sodium cell at 50 °C. From the 3^rd to 50^th cycle, the capacity fading is only 0.14% per cycle (from 388 mAh g^?1 at 3^rd the cycle to 360 mAh g^?1 at the 50^th cycle), demonstrating superior cyclability. A high energy density of 650 Wh kg^?1 is obtained at the material level. The reaction mechanism studies of FeO_0.7F_1.3/C with sodium show a hybridized mechanism of both intercalation and conversion reaction.     

Reorientation patterns in central-place foraging: internal clocks and klinokinesis

We study central-place foraging patterns of Aphaenogaster senilis ants at a population level by video framing individual ant trajectories in a circular arena with a nest connected to its centre. The ants naturally leave and enter the nest and forage generating non-trivial movement patterns around the nest. Our data analysis indicated that the trajectories observed can be classified into two strategies: the risk-averse strategy, which involves wandering around the nest without departing far from it and the risk-prone strategy, which involves long exploration paths with periodic returns to the central region, nearby the nest. We found that both risk-prone and risk-averse strategies exhibit qualitatively the same reorientation patterns, with the time between consecutive reorientations covering a wide range of scales, and fitting a stretched exponential function. Nevertheless, differences in the temporal scales and the time variability of such reorientation events differ, together with other aspects of motion, such as average speed and turns. Our results give experimental evidence that the internal mechanisms driving reorientations in ants tend to favour frequently long relocations, as theory predicts for efficient exploration in patchy landscapes, but ants engaged in central-place foraging can modulate such behaviour to control distances from the nest. Previous works on the species support the idea that risk-prone and risk-averse strategies may reflect actual differences between individuals age and experience; these factors (age and experience) should be then relevant in modulating the internal reorientation clocks. To support the validity of our findings, we develop a random-walk model combining stretched exponential reorientation clocks with klinokinesis that fits the time length and the travelled distance distributions of the observed trajectories.     

Supervised image segmentation using Q-Shift Dual-Tree Complex Wavelet Transform coefficients with a texton approach

In this study, we propose a simple and efficient texture-based algorithm for image segmentation. This method constitutes computing textons and bag of words (BOWs) learned by support vector machine (SVM) classifiers. Textons are composed of local magnitude coefficients that arise from the Q-Shift Dual-Tree Complex Wavelet Transform (DT-CWT) combined with color components. In keeping with the needs of our research context, which addresses land cover mapping from remote images, we use a few small texture patches at the training stage, where other supervised methods usually train fully representative textures. We accounted for the scale and rotation invariance issue of the textons, and three different invariance transforms were evaluated on DT-CWT-based features. The largest contribution of this study is the comparison of three classification schemes in the segmentation algorithm. Specifically, we designed a new scheme that was especially competitive and that uses several classifiers, with each classifier adapted to a specific size of analysis window in texton quantification and trained on a reduced data set by random selection. This configuration allows quick SVM convergence and an easy parallelization of the SVM-bank while maintaining a high segmentation accuracy. We compare classification results with textons made using the well-known maximum response filters bank and speed up robust features features as references. We show that DT-CWT textons provide better distinguishing features in the entire set of configurations tested. Benchmarks of our different method configurations were made over two substantial textured mosaic sets, each composed of 100 grey or color mosaics made up of Brodatz or VisTex textures. Lastly, when applied to remote sensing images, our method yields good region segmentation compared to the ENVI commercial software, which demonstrates that the method could be used to generate land cover maps and is suitable for various purposes in image segmentation.     

Is It Possible to Retain Customer Loyalty When a Service Has Failed?

This article aims to analyze the impact of recovery on loyalty in the context of a service chain characterized by the e‐quality–perceived value–loyalty relationship. A sample of 91 out of 1,201 respondents claimed to have had service problems with an online travel agency website. A causal model to test relationships was performed using structural equations modeling, and it was found that data fit with the proposed model. The really important point to retaining customers is quality. It is not so clear that the recovery effort might affect loyalty. Our findings underpin some previous stream of literature confirming that recovery does not always affect loyalty. Although the literature has not reached a consensus in this topic, we add new elements in this debate.     

High-dimensional MRI data analysis using a large-scale manifold learning approach

A novel manifold learning approach is presented to efficiently identify low-dimensional structures embedded in high-dimensional MRI data sets. These low-dimensional structures, known as manifolds, are used in this study for predicting brain tumor progression. The data sets consist of a series of high-dimensional MRI scans for four patients with tumor and progressed regions identified. We attempt to classify tumor, progressed and normal tissues in low-dimensional space. We also attempt to verify if a progression manifold exists—the bridge between tumor and normal manifolds. By identifying and mapping the bridge manifold back to MRI image space, this method has the potential to predict tumor progression. This could be greatly beneficial for patient management. Preliminary results have supported our hypothesis: normal and tumor manifolds are well separated in a low-dimensional space. Also, the progressed manifold is found to lie roughly between the normal and tumor manifolds.