Discovery of a potent and highly β1 specific proteasome inhibitor from a focused library of urea-containing peptide vinyl sulfones and peptide epoxyketones

Syringolins, a class of natural products, potently and selectively inhibit the proteasome and show promising antitumour activity. To gain insight in the mode of action of syringolins, the ureido structural element present in syringolins is incorporated in oligopeptide vinyl sulfones and peptide epoxyketones yielding a focused library of potent new proteasome inhibitors. The distance of the ureido linkage with respect to the electrophilic trap strongly influences subunit selectivity within the proteasome. Compounds 13 and 15 are β5 selective and their potency exceeds that of syringolin A. In contrast, 5 may well be the most potent β1 selective compound active in living cells reported to date.     

An evolutionary algorithm for de novo optimization of functional transition metal compounds

Development of functional inorganic and transition metal compounds is usually based on ad hoc qualified guesses, with computational methods playing a lesser role than in drug discovery. A de novo evolutionary algorithm (EA) is presented that automatically generates transition metal complexes using a search space constrained around chemically meaningful structures assembled from three kinds of fragments: a part shared by all structures and typically containing the metal center itself, one or several parts consisting of ligand skeletons, and unconstrained parts that may grow and vary freely. In EA optimizations, using a cost-efficient fitness function based on a linear quantitative structure-activity relationship model for catalytic activity, we demonstrate the capabilities of the method by retracing the transition from the first-generation, phosphine-based Grubbs olefin metathesis catalysts to second-generation catalysts containing N-heterocyclic carbene ligands instead of phosphines. Moreover, DFT calculations on selected high-fitness, last-generation structures from these evolutionary experiments suggest that, in terms of catalytic activity, the structures arrived at by virtual evolution alone compare favorably with existing, highly active catalysts. The structures from the evolution experiments are, however, complex and probably difficult to synthesize, but a set of manually simplified variations thereof might form the leads for a new generation of Grubbs catalysts.     

New insights into churn prediction in the telecommunication sector: A profit driven data mining approach

Customer churn prediction models aim to indicate the customers with the highest propensity to attrite, allowing to improve the efficiency of customer retention campaigns and to reduce the costs associated with churn. Although cost reduction is their prime objective, churn prediction models are typically evaluated using statistically based performance measures, resulting in suboptimal model selection. Therefore, in the first part of this paper, a novel, profit centric performance measure is developed, by calculating the maximum profit that can be generated by including the optimal fraction of customers with the highest predicted probabilities to attrite in a retention campaign. The novel measure selects the optimal model and fraction of customers to include, yielding a significant increase in profits compared to statistical measures.In the second part an extensive benchmarking experiment is conducted, evaluating various classification techniques applied on eleven real-life data sets from telecom operators worldwide by using both the profit centric and statistically based performance measures. The experimental results show that a small number of variables suffices to predict churn with high accuracy, and that oversampling generally does not improve the performance significantly. Finally, a large group of classifiers is found to yield comparable performance.     

An unconditionally stable time-domain discretization on cartesian meshes for the simulation of nonuniform magnetized cold plasma

In this paper an unconditionally stable, spatially and temporally implicit time-domain discretization for nonuniform magnetized cold plasma is developed. The discrete dispersion relation is free of spurious solutions and approximates the continuous dispersion relation for well-resolved wavelengths and frequencies (kΔ ? π, ωΔ_t ? π). For a specific choice of parameters, the discrete dispersion relation approximates the continuous dispersion relation for all wavelengths and frequencies up to the Nyquist limit. A few examples, amongst them one involving mode conversion, illustrate the new method.     

Developing homogeneous isotropic turbulence

We investigate the self-similar evolution of the transient energy spectrum, which precedes the establishment of the Kolmogorov spectrum in homogeneous isotropic turbulence in three dimensions using the EDQNM closure model. The transient evolution exhibits self-similarity of the second kind and has a non-trivial dynamical scaling exponent, which results in the transient spectrum having a scaling that is steeper than the Kolmogorov k^−5/3 spectrum. Attempts to detect a similar phenomenon in DNS data are inconclusive, owing to the limited range of scales available.     

Emerging applications of wavelets: A review

Although most of its popular applications have been in discrete-time signal processing for over two decades, wavelet transform theory offers a methodology to generate continuous-time compact support orthogonal filter banks through the design of discrete-time finite length filter banks with multiple time and frequency resolutions. In this paper, we first highlight inherently built-in approximation errors of discrete-time signal processing techniques employing wavelet transform framework. Then, we present an overview of emerging analog signal processing applications of wavelet transform along with its still active research topics in more matured discrete-time processing applications. It is shown that analog wavelet transform is successfully implemented in biomedical signal processing for design of low-power pacemakers and also in ultra-wideband (UWB) wireless communications. The engineering details of analog circuit implementation for these continuous-time wavelet transform applications are provided for further studies. We expect a flurry of new research and technology development activities in the coming years utilizing still promising and almost untapped analog wavelet transform and multiresolution signal representation techniques.     

Thermosensitive polymer structures based on segmented copolymer networks

Segmented polymer networks with LCST‐behavior have been prepared by free radical initiated copolymerization of α,ω‐bis‐methacrylate terminated poly(methyl vinyl ether) (PMVE) with 2‐hydroxy ethyl methacrylate (HEMA) or butyl acrylate (BA). The PMVE bis‐macromonomers have been obtained via a semi‐continuous process by end‐capping the living cationic polymerization of methyl vinyl ether (MVE) with HEMA. The phase separation temperature can be varied by changing the PMVE/comonomer ratio. Incorporation of PMVE‐grafts in the hydrogels increases the rate of deswelling and improves the mechanical properties. The application of the segmented networks for thermo‐controllable solid phase extraction has been demonstrated by their thermosensitive adsorption behavior of toluene from a water solution.     

Poly(vinyl ethers) as building blocks for new materials

The living cationic polymerization of vinyl ethers has been used to prepare a number of new polymers with special properties. Sequential polymerization of the hydrophilic methyl vinyl ether (MVE) and the hydrophobic octadecyl vinyl ether (ODVE) has lead to amphiphilic block-copolymers with emulsifying properties for water/decane mixtures. Poly(vinyl-ether) macromonomers were obtained by end-capping of living polymers with hydroxyethyl acrylate. Copolymerization of polyODVE-macromonomer with usual acrylates lead to highly branched hydrophobic polymers. When the end-capping was performed with bifunctionally living polymers, the corresponding “bis-macromonomers” were obtained. Copolymerization of such bis-macromonomers with styrene or butyl acrylate, leads to the formation of segmented polymer networks. In the case of polyODVE-poly(butyl acrylate), these networks showed a pronounced phase separation. Due to the crystallinity of the polyODVE domains, these materials showed shape memory properties.     

Retrial queues with balanced call blending: analysis of single-server and multiserver model

In call centers, call blending consists in the mixing of incoming and outgoing call activity, according to some call blending balance. Recently, Artalejo and Phung-Duc have developed an apt model for such a setting, with a two way communication retrial queue. However, by assuming a classical (proportional) retrial rate for the incoming calls, the short-term blending balance is heavily impacted by the number of incoming calls, which may be undesired, especially when the balance between incoming and outgoing calls is vital to the service offered. In this contribution, we consider an alternative to classical call blending, through a retrial queue with constant retrial rate for incoming calls. For the single-server case (one operator), a generating functions approach enables to derive explicit formulas for the joint stationary distribution of the number of incoming calls and the system state, and also for the factorial moments. This is complemented with a stability analysis, expressions for performance measures, and also recursive formulas, allowing reliable numerical calculation. A correlation study enables to study the system’s short-term blending balance, allowing to compare it to that of the system with classical retrial rate. For the multiserver case (multiple operators), we provide a quasi-birth-and-death process formulation, enabling to derive a sufficient and necessary condition for stability in this case (in a simple form), a numerical recipe to obtain the stationary distribution, and a cost model.