Tunable Bidirectional Electroosmotic Flow for Diffusion-Based Separations

We present a new concept for on-chip separation that leverages bidirectional flow, to tune the dispersion regime of molecules and particles. The system can be configured so that low diffusivity species experience a ballistic transport regime and are advected through the chamber, whereas high diffusivity species experience a diffusion dominated regime with zero average velocity and are retained in the chamber. We detail the means of achieving bidirectional electroosmotic flow using an array of alternating current (AC) field-effect electrodes, experimentally demonstrate the separation of particles and antibodies from dyes, and present a theoretical analysis of the system, providing engineering guidelines for its design and operation.     

Psychogenic Voice Disorders in Performers: A Psychodynamic Model

Psychogenic voice disorders are not infrequently encountered in the busy voice clinic. A clinician-friendly psychodynamic model and a multidisciplinary management approach are presented which have proven helpful for our voice team and our patients. In essence the formulation revolves around an “event” occurring, which may be either organic or psychological in nature. The ensuing dysphonia then leads to emotional consequences which in turn have physical consequences on the vocal tract. The situation can become reinforcing and illness behaviors develop. Elucidating this event/process to the patient improves the likelihood of a successful long-term outcome. The diagnostic and management roles of the various team members are discussed.     

Synthesis of isomerically pure anti-anthradithiophene derivatives

The regiospecific total synthesis and characterization of anti-isomers of 2,8-dialkylanthradithiophenes are described. The "anti" structure of the ADT derivatives is demonstrated by (13)C NMR as well as single crystal X-ray diffraction.     

Incorporation of carbon nanotubes in a silica HPLC column to enhance the chromatographic separation of peptides: theoretical and practical aspects

The retention mechanism of a series of peptides on a single-wall carbon nanotube (SWCNT) stationary phase inside an HPLC column was investigated over a wide range of mobile phase compositions. While the similar size C18 column exhibited an efficiency of 11.5 μm, the SWCNT column increased the efficiency, i.e. 7.10 μm at a flow rate of 0.8 mL/min, and significantly affected the separation quality of the peptides. The values of enthalpy (ΔH) and entropy (ΔS(*)) of transfer of the peptides from the mobile to the SWCNT stationary phase were determined. The method studied each factor, i.e. ACN fraction x in the ACN/water mixture and column temperature. The changes in retention factor, ΔH and ΔS(*) as a function of the ACN fraction in the mobile phase were examined. These variations are explained using the organization of ACN in clusters in the ACN/water mixture and on the steric and electronic forces implied in the retention process. The information obtained in this work makes this SWCNT stationary phase useful for peptide research and demonstrated the role of ACN to improve the separation quality.     

Logical analysis of data: classification with justification

Learning from examples is a frequently arising challenge, with a large number of algorithms proposed in the classification, data mining and machine learning literature. The evaluation of the quality of such algorithms is frequently carried out ex post, on an experimental basis: their performance is measured either by cross validation on benchmark data sets, or by clinical trials. Few of these approaches evaluate the learning process ex ante, on its own merits. In this paper, we discuss a property of rule-based classifiers which we call “justifiability”, and which focuses on the type of information extracted from the given training set in order to classify new observations. We investigate some interesting mathematical properties of justifiable classifiers. In particular, we establish the existence of justifiable classifiers, and we show that several well-known learning approaches, such as decision trees or nearest neighbor based methods, automatically provide justifiable classifiers. We also identify maximal subsets of observations which must be classified in the same way by every justifiable classifiers. Finally, we illustrate by a numerical example that using classifiers based on “most justifiable” rules does not seem to lead to overfitting, even though it involves an element of optimization.     

A ranking model in uncertain, imprecise and multi-experts contexts: The application of evidence theory

We consider ranking problems where the actions are evaluated on a set of ordinal criteria. The evaluation of each alternative with respect to each criterion may be imperfect and is provided by one or several experts. We model each imperfect evaluation as a basic belief assignment (BBA). In order to rank the BBAs characterizing the performances of the actions according to each criterion, a new concept called RBBD and based on the comparison of these BBAs to ideal or nadir BBAs is proposed. This is performed using belief distances that measure the dissimilarity of each BBA to the ideal or nadir BBAs. A model inspired by Xu et al.’s method is also proposed and illustrated by a pedagogical example.     

Iterative algorithm for spatial and intensity normalization of MEMRI images. Application to tract-tracing of rat olfactory pathways

Manganese (Mn)-enhanced magnetic resonance imaging (MEMRI) is an emerging technique for visualizing neuronal pathways and mapping brain activity modulation in animal models. Spatial and intensity normalizations of MEMRI images acquired from different subjects are crucial steps as they can influence the results of groupwise analysis. However, no commonly accepted procedure has yet emerged. Here, a normalization method is proposed that performs both spatial and intensity normalizations in a single iterative process without the arbitrary choice of a reference image. Spatial and intensity normalizations benefit from this iterative process. On one hand, spatial normalization increases the accuracy of region of interest (ROI) positioning for intensity normalization. On the other hand, improving the intensity normalization of the different MEMRI images leads to a better-averaged target on which the images are spatially registered. After automatic fast brain segmentation and optimization of the normalization process, this algorithm revealed the presence of Mn up to the posterior entorhinal cortex in a tract-tracing experiment on rat olfactory pathways. Quantitative comparison of registration algorithms showed that a rigid model with anisotropic scaling is the best deformation model for intersubject registration of three-dimensional MEMRI images. Furthermore, intensity normalization errors may occur if the ROI chosen for intensity normalization intersects regions where Mn concentration differs between experimental groups. Our study suggests that cross-comparing Mn-injected animals against a Mn-free group may provide a control to avoid bias introduced by intensity normalization quality. It is essential to optimize spatial and intensity normalization as the detectability of local between-group variations in Mn concentration is directly tied to normalization quality.     

Redox-fixable manipulation of planar chirality in late transition metal sandwich compounds; a 1,1'-diphosphacobaltocene/1,1'-diphosphacobaltocenium salt couple

An electrochemically switched face inversion process for η(5)-coordinated ligands in late transition metal sandwich complexes is demonstrated.     

Palladium-catalyzed stereoconvergent formylation of (E/Z)-β-bromo-β-fluorostyrenes: straightforward access to (Z)-α-fluorocinnamic aldehydes and (Z)-β-fluorocinnamic alcohols

We report here the stereoconvergent formylation of (E/Z)-β-bromo-β-fluorostyrene mixtures with carbon monoxide and sodium formate catalyzed by palladium. Optimization of reaction conditions leads to the corresponding pure (Z)-α-fluorocinnamaldehydes in good yields. The reaction was extended to styrenes bearing electro-attracting or electro-donating groups. The obtained α-fluoroaldehydes were smoothly reduced to the corresponding (Z)-β-fluorocinnamic alcohol by NaBH(4). The reaction could be performed on functionalized substrates as demonstrated by the access to the glucoside of β-fluoroconiferyl alcohol, (Z)-β-fluoroconiferin, a strong inhibitor of lignin polymerization.