Prostaglandins suppress an outward potassium current in embryonic rat sensory neurons

One of the challenges in understanding ciliary and flagellar motility is determining the mechanisms that locally regulate dynein-driven microtubule sliding. Our recent studies demonstrated that microtubule sliding, in Chlamydomonas flagella, is regulated by phosphorylation. However, the regulatory proteins remain unknown. Here we identify the 138-kD intermediate chain of inner arm dynein I1 as the critical phosphoprotein required for regulation of motility. This conclusion is founded on the results of three different experimental approaches. First, genetic analysis and functional assays revealed that regulation of microtubule sliding, by phosphorylation, requires inner arm dynein I1. Second, in vitro phosphorylation indicated the 138-kD intermediate chain of I1 is the only phosphorylated subunit. Third, in vitro reconstitution demonstrated that phosphorylation and dephosphorylation of the 138-kD intermediate chain inhibits and restores wild-type microtubule sliding, respectively. We conclude that change in phosphorylation of the 138-kD intermediate chain of I1 regulates dynein-driven microtubule sliding. Moreover, based on these and other data, we predict that regulation of I1 activity is involved in modulation of flagellar waveform.     

Mode-specific strategy for controlling a single-molecule reaction

Inelastic tunnelling electrons are a proper excitation source to induce chemical transformations on a single adsorbate. When their energy is tuned to that of molecular vibrational states, the modification may follow complex internal vibrational pathways. Here, we analyse our recent results on the selective excitation of ammonium stretching or bending modes to control the outcome of a simple bond-cleavage reaction. With the help of model calculations, we provide a detailed molecular-scale picture of the competing internal pathways leading to molecular movement. A mode-selective strategy, based on local excitations of specific reaction coordinates, has an important drawback when applied to adsorbate systems due to the problem of fast energy randomization. The success of such a mode-selective strategy is determined here by the ability of the scanning tunnelling microscope to study reactivity in the limit of very low yield and very low power irradiation, in a regime where vibrational heating of the adsorbate/surface system becomes negligible.     

Vinyltrimethylsilane-co-N-vinyl-2-pyrrolidone and vinyltrimethoxysilane-co-N-vinyl-2-pyrrolidone copolymers Synthesis and reactivity ratios

Summary Copolymers containing vinyltrimethylsilane and vinyltrimethoxysilane with N-vinyl-2-pyrrolidone at different compositions were synthesized and characterized. The reactivity ratios was estimated by using the classical Fineman-Ross and Kelen Tüdos linear fitting procedures. These parameters were also estimated through a computer program based on nonlinear minimization algorithm, starting from the r₁ and r₂ values obtained by the former procedures. The analysis of the results allow us to interpret the reactivity behaviour of these polymers in terms of the relative reactivity of the substiuents. The effect of the chemical structure of the polymer side group is discussed in terms of the different contributions to the stabilization of the radical intermediates. Received: 18 February 1998/Revised version: 11 March 1998/Accepted: 16 March 1998     

The effect of surface roughness on condensing steam

Heal transfer coefficients for steam condensing on the outside of a smooth, and three artificially roughened pipes have been obtained for a condensate film Reynolds Number range of 1,500 to 9,000. Dimensionless local and mean heat transfer coefficient are presented, and in all cases significant increases in tht coefficients for the rough pipes are observed.     

Vinyltrimethoxysilane-co-2-vinylpyridine copolymer Synthesis and monomer reactivity ratios

Summary Copolymers containing vinyltrimethoxysilane (VTMOS) and 2-vinylpyridine (2VPy) at different compositions were synthesized and characterized. The monomer reactivity ratios r₁ and r₂ were estimated by using the classical Fineman-Ross and Kelen Tüdos linear fitting procedures. Moreover, these parameters were also estimated using a nonlinear computational fitting known as Reactivity Ratios Error in Variable Method (RREVM). Attempts to obtain the corresponding copolymer with vinyltrimethylsilane (VTMS) were performed but only hompolymerization 2VPy is observed due to the non-reactivity of VTMS under this conditions. The results were analysed in terms of the relative comonomeric structures and compared with similar related systems. The reactivities are interpreted in terms of the resonance and stabilization effects together with the chemical structure. Received: 22 April 1999/Revised version: 26 July 1999/Accepted: 27 July 1999     

Aromatic volatile organic compounds absorption with phenyl-based deep eutectic solvents: A molecular thermodynamics and dynamics study

The suitability of phenyl-based deep eutectic solvents (DESs) as absorbents for toluene absorption was investigated by means of thermodynamic modeling and molecular dynamics (MD). The thermodynamic models perturbed-chain statistical associating fluid theory (PC-SAFT) and conductor-like screening model for real solvents (COSMO-RS) were used to predict the vapor–liquid equilibrium of DES–toluene systems. PC-SAFT yielded quantitative results even without using any binary fitting parameters. Among the five DESs studied in this work, [TEBAC][PhOH] consisting of triethyl benzyl ammonium chloride (TEBAC) and phenol (PhOH), was considered as the most suitable absorbent. Systems with [TEBAC][PhOH] had lowest equilibrium pressures of the considered DES–toluene mixtures, the best thermodynamic characteristics (i.e., Henry's law constant, excess enthalpy, Gibbs free energy of solvation of toluene), and the highest self-diffusion coefficient of toluene. The molecular-level mechanism was explored by MD simulations, indicating that [TEBAC][PhOH] has the strongest interaction of DES–toluene compared to the other DESs under study. This work provides guidance to rationally design novel DESs for efficient aromatic volatile organic compounds absorption.     

Trickle flow hydrodynamic multiplicity: Experimental observations and pore-scale capillary mechanism

Trickle bed reactors are encountered throughout the process industry. Considerable attention has been given to the study of the hydrodynamics of this type reactor. It has been identified that, in the trickle flow regime, the hydrodynamic parameters (e.g. pressure drop and liquid holdup) are not unique functions of the operating and system conditions, but depend on the flow history. This study reviews the experimental trends identified in literature on the basis of a limiting cases framework and then evaluates the three-dimensional pore-scale liquid distribution using computed tomography (CT) data. This leads to the identification of 20 phenomenological trends that characterize hydrodynamic multiplicity, including hydrodynamic flow hysteresis as well as the effects of pre-wetting. The CT study yields additional experimental insight into the role of capillary pressure and ultimately leads to the proposal of a capillary gate mechanism based on contact angle hysteresis as the root cause of multiplicity. The mechanism is incorporated into a simple pore-network model. It is shown that the qualitative performance of the model corresponds closely to the majority of phenomenological trends and is capable of explaining the observed experimental behaviour.     

Constructing ensembles of classifiers using supervised projection methods based on misclassified instances

In this paper, we propose an approach for ensemble construction based on the use of supervised projections, both linear and non-linear, to achieve both accuracy and diversity of individual classifiers. The proposed approach uses the philosophy of boosting, putting more effort on difficult instances, but instead of learning the classifier on a biased distribution of the training set, it uses misclassified instances to find a supervised projection that favors their correct classification. We show that supervised projection algorithms can be used for this task. We try several known supervised projections, both linear and non-linear, in order to test their ability in the present framework. Additionally, the method is further improved introducing concepts from oversampling for imbalance datasets. The introduced method counteracts the negative effect of a low number of instances for constructing the supervised projections.The method is compared with AdaBoost showing an improved performance on a large set of 45 problems from the UCI Machine Learning Repository. Also, the method shows better robustness in presence of noise with respect to AdaBoost.