Copper (II) adsorption capacity of a novel hydroxytyrosol-based polyacrylate

A novel hydroxytyrosol-based polyacrylate polymer material (pAcHTy) endowed with metal ion adsorption ability was obtained by free radical polymerization of a monomer containing a hydroxytyrosol precursor (tyrosol). Hydroxytyrosol (HTy) is the main natural polyphenolic compound with antioxidant activity occurring in virgin olive oil and in olive oil wastewaters. pAcHTy showed a good chelating activity with respect to Cu²⁺ ions, especially at pH 6 where short equilibrium times and high adsorption capacity were observed (146 mg/g). From thermodynamic parameters, it has been found that the sorption process was spontaneous at low temperature and exothermic in nature. The adsorption process has been studied by employing three simplified kinetic models, including a pseudo-first-order equation, pseudo-second-order equation, and intraparticle diffusion equation. Kinetic parameters, rate constants, equilibrium sorption capacities, and related correlation coefficients, for each kinetic model, were calculated and discussed. It was shown that the adsorption of Cu²⁺ ions could be described by the pseudo-second-order equation, suggesting that the adsorption process is presumable a chemisorption. The pAcHTy polymer could find an important application in the medical field, particularly in chelation therapy as well as in the wastewater and drinking water treatment plants.     

A regioregular polythiophene–fullerene for polymeric solar cells

In this article, we present the synthesis and characterization of a new thiophenic copolymer bearing the C₆₀ fullerene directly linked to the end of a hexamethylenic side chain. This copolymer was prepared with good yield using a simple and straightforward post‐polymerization functionalization procedure applied on a soluble regioregular polymeric precursor obtained by regiospecific organometallic coupling. Copolymer structural and photophysical properties were investigated by gel permeation chromatography, thermal analysis (DSC and TGA), NMR, IR, UV–Vis, and atomic force spectroscopy. The double‐cable copolymer possesses good solubility in common organic solvents, high filmability, thermal stability, and low segmental aggregation tendency. It was tested as a photoactive layer in a polymeric solar cell showing a power conversion efficiency under 100 mW cm^?2 AM 1.5 illumination higher than 4%, more than that of the reference cell made with the conventionally used P3HT/PCBM blend. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42121.     

The conservation of poly-A-containing RNA during the dormant state of the moss Polytrichum commune

The moss Polytrichum commune can be dried to less than 2% of free water and kept for some weeks without losing its viability. Upon rehydration of the moss, protein synthesis starts about 60 minutes before incorporation of radioactive precursors into RNA can be observed. Pulse labeled total RNA and poly-A-containing RNA do not show quantitative or qualitative alterations during desiccation up to 20 days.     

The monosaccharide binding site of lentil lectin: an X-ray and molecular modelling study

The X-ray crystal structure of lentil lectin in complex with alpha-D-glucopyranose has been determined by molecular replacement and refined to an R-value of 0.20 at 3.0 A resolution. The glucose interacts with the protein in a manner similar to that found in the mannose complexes of concanavalin A, pea lectin and isolectin I from Lathyrus ochrus. The complex is stabilized by a network of hydrogen bonds involving the carbohydrate oxygens O6, O4, O3 and O5. In addition, the alpha-D-glucopyranose residue makes van der Waals contacts with the protein, involving the phenyl ring of Phe123 beta. The overall structure of lentil lectin, at this resolution, does not differ significantly from the highly refined structures of the uncomplexed lectin. Molecular docking studies were performed with mannose and its 2-O and 3-O-m-nitro-benzyl derivatives to explain their high affinity binding. The interactions of the modelled mannose with lentil lectin agree well with those observed experimentally for the protein-carbohydrate complex. The highly flexible Me-2-O-(m-nitro-benzyl)-alpha-D-mannopyranoside and Me-3-O-(m-nitro-benzyl)-alpha-D-mannopyranoside become conformationally restricted upon binding to lentil lectin. For best orientations of the two substrates in the combining site, the loss of entropy is accompanied by the formation of a strong hydrogen bond between the nitro group and one amino acid, Gly97 beta and Asn125 beta, respectively, along with the establishment of van der Waals interactions between the benzyl group and the aromatic amino acids Tyr100 beta and Trp128 beta.     

Computing effective properties of random heterogeneous materials on heterogeneous parallel processors

In recent decades, finite element (FE) techniques have been extensively used for predicting effective properties of random heterogeneous materials. In the case of very complex microstructures, the choice of numerical methods for the solution of this problem can offer some advantages over classical analytical approaches, and it allows the use of digital images obtained from real material samples (e.g., using computed tomography). On the other hand, having a large number of elements is often necessary for properly describing complex microstructures, ultimately leading to extremely time-consuming computations and high memory requirements. With the final objective of reducing these limitations, we improved an existing freely available FE code for the computation of effective conductivity (electrical and thermal) of microstructure digital models. To allow execution on hardware combining multi-core CPUs and a GPU, we first translated the original algorithm from Fortran to C, and we subdivided it into software components. Then, we enhanced the C version of the algorithm for parallel processing with heterogeneous processors. With the goal of maximizing the obtained performances and limiting resource consumption, we utilized a software architecture based on stream processing, event-driven scheduling, and dynamic load balancing. The parallel processing version of the algorithm has been validated using a simple microstructure consisting of a single sphere located at the centre of a cubic box, yielding consistent results. Finally, the code was used for the calculation of the effective thermal conductivity of a digital model of a real sample (a ceramic foam obtained using X-ray computed tomography). On a computer equipped with dual hexa-core Intel Xeon X5670 processors and an NVIDIA Tesla C2050, the parallel application version features near to linear speed-up progression when using only the CPU cores. It executes more than 20 times faster when additionally using the GPU.     

Designing an MOOC as an agent-platform aggregating heterogeneous virtual learning environments

ABSTRACT

With the emergence of cloud technologies, on the one hand, and social networks, on the other hand, the possibilities for e-learning have been drastically enhanced in the latest years. Virtual Learning Environments (VLE) can now indeed contain a huge amount of learning resources; in parallel, large user communities are available in social networks. These nevertheless remain different systems but, by using these heterogeneous software environments together, the possibilities for interaction could be multiplied. That is why, this paper suggests to build a Massive Open Online Course (MOOC) environment through a Multi-Agent System (MAS) working as a virtual abstraction layer over heterogeneous software platforms. The idea is to aggregate different traditional VLE to dispose of the learning objects they own as well as other platforms such as social networks to furnish an easy access to the MOOC of their large user communities. The MAS design has been architectured around a real-life organisational pattern – the joint venture – allowing one to deal with the complexity of heterogeneous software environments in a manner that real-life companies set up joint governance. Communication scenarios issued of a field analysis are pointed out in the paper; these are supported by the MOOC platform in the native environment as well as in Facebook. The proposal is indeed validated through the development of a prototype using Facebook as a case study for third-party platform interfacing. We finally highlight the benefits for the user experience.     

Comments on the hierarchically structured bin packing problem

We study the hierarchically structured bin packing problem. In this problem, the items to be packed into bins are at the leaves of a tree. The objective of the packing is to minimize the total number of bins into which the descendants of an internal node are packed, summed over all internal nodes. We investigate an existing algorithm and make a correction to the analysis of its approximation ratio. Further results regarding the structure of an optimal solution and a strengthened inapproximability result are given.     

A new encoding technique for peptide classification

Research on peptide classification problems has focused mainly on the study of different encodings and the application of several classification algorithms to achieve improved prediction accuracies. The main drawback of the literature is the lack of an extensive comparison among the available encoding methods on a wide range of classification problems. This paper addresses the fundamental issue of which peptide encoding promises the best results for machine learning classifiers. Two novel encoding methods based on physicochemical properties of the amino acids are proposed and an extensive comparison with several standard encoding methods is performed on three different classification problems (HIV-protease, recognition of T-cell epitopes and prediction of peptides that bind human leukocyte antigens). The experimental results demonstrate the effectiveness of the new encodings and show that the frequently used orthonormal encoding is inferior compared to other methods.