Synthesis and crystal structure of a new lithium cyclohexaphosphate hydrate: Li6P6O18·10H2O

The synthesis and crystal structure of a novel hydrate of lithium cyclohexaphosphate are reported. Li₆P₆O₁₈·10H₂O crystallizes in the space group C2/c with a = 15.113(5), b = 12.006(2), c = 15.892(2) Å, = 122.85(2)°, and Z = 4. The structure consists of P₆O₁₈ ring layers stacked along the c direction in between which are located the lithiumions and water molecules. Two LiO₄ tetrahedra share common edges with LiO₅ pseudosquare pyramids to form two independant Li₃O₉ units. About 50% of the water molecules have fractional occupancy rates and form fragments of molecules. A linear relationship is established between the relative cell volume V/Z and the hydration degree, n, for all the known hydrates: Li₆P₆O₁₈·nH₂O.     

The stochastic bid generation problem in combinatorial transportation auctions

In this paper, we deal with the generation of bundles of loads to be submitted by carriers participating in combinatorial auctions in the context of long-haul full truckload transportation services. We develop a probabilistic optimization model that integrates the bid generation and pricing problems together with the routing of the carrier’s fleet. We propose two heuristic procedures that enable us to solve models with up to 400 auctioned loads.     

Optimization of a linear function over the set of stochastic efficient solutions

In this paper we study the problem of optimization over an integer efficient set of a Multiple Objective Integer Linear Stochastic Programming problem. Once the problem is converted into a deterministic one by adapting the $2$ -levels recourse approach, a new pivoting technique is applied to generate an optimal efficient solution without having to enumerate all of them. This method combines both techniques, the L-shaped method and the combined method developed in Chaabane and Pirlot (J Ind Manag Optim 6:811–823, 2010). A detailed didactic example is given to illustrate different steps of our algorithm.     

Enhancing techniques for learning decision trees from imbalanced data

Advances in Data Analysis and Classification - Several machine learning techniques assume that the number of objects in considered classes is approximately similar. Nevertheless, in real-world...     

Enhanced functional properties of chitosan films cross-linked by biosourced dicarboxylic acids

Chitosan-based films were developed using different biosourced dicarboxylic acid solutions (succinic acid, adipic acid, suberic acid and sebacic acid). The effect of incorporating these nontoxic solutions on water vapor barrier, tensile and antimicrobial properties of chitosan films was evaluated. Fourier Transform Infrared (FTIR) and cross polarization magic angle spinning (CP/MAS) nuclear magnetic resonance (NMR) analyses were also performed to investigate functional groups interactions between chitosan and dicarboxylic acids. Acetic acid-chitosan films showed significantly higher water vapor permeability (WVP) and lower tensile strength (TS) and elongation at break (%E) than dicarboxylic acid-prepared films (p < 0.05). Using either adipic acid or suberic acid solutions to fabricate chitosan films reduced WVP by 85% and enhanced TS by 21 to 27% and %E by more than 60% when compared with the acetic acid-prepared films. Chitosan films modified with either adipic acid or suberic acid exhibited antimicrobial activity against all tested microorganisms.     

Topological approach to solve frame structures using topological collections and transformations

The present work tackled the modeling of frame structures using a topological approach based on the concepts of topological collections and transformations. The topological collections are used to specify the interconnection law between the frame structures and the transformations that are used to describe their behavior. As a language allowing the application of this approach, we applied the MGS (Modeling of General System) language. To validate this approach, we studied the case of two- and three-dimensional frame structures. Then, the results obtained using the MGS language are presented and compared to those obtained by the structural calculation software by the finite-element method RDM6. For both studied cases, we find that the results obtained by MGS language based on the notions of topological collections and transformations and those obtained by the RDM6 software based on the finite element method are very close, which validates our approach. Using this topological approach, any structure can be characterized by local relations between its elements, thus making it possible to dissociate its topology and its physics. Indeed, in our topological approach, we separately define the topology of the studied frame structure and the local behavior law as well as the equilibrium equations of its various components. Therefore, this topological approach might be generalized to model complex systems which can be considered as a set of local elements linked by a neighborhood relationship.     

Cu-Doped ZnO Nanoparticles for Non-Enzymatic Glucose Sensing

Copper-doped zinc oxide nanoparticles (NPs) Cu_xZn_1−xO (x = 0, 0.01, 0.02, 0.03, and 0.04) were synthesized via a sol-gel process and used as an active electrode material to fabricate a non-enzymatic electrochemical sensor for the detection of glucose. Their structure, composition, and chemical properties were characterized using X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier-transform infrared (FTIR) and Raman spectroscopies, and zeta potential measurements. The electrochemical characterization of the sensors was studied using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and differential pulse voltammetry (DPV). Cu doping was shown to improve the electrocatalytic activity for the oxidation of glucose, which resulted from the accelerated electron transfer and greatly improved electrochemical conductivity. The experimental conditions for the detection of glucose were optimized: a linear dependence between the glucose concentration and current intensity was established in the range from 1 nM to 100 μM with a limit of detection of 0.7 nM. The proposed sensor exhibited high selectivity for glucose in the presence of various interfering species. The developed sensor was also successfully tested for the detection of glucose in human serum samples.     

Fluorinated PLGA Nanoparticles for Enhanced Drug Encapsulation and 19F NMR Detection

In the continuous search for multimodal systems with combined diagnostic and therapeutic functions, several efforts have been made to develop multifunctional drug delivery systems. In this work, through a covalent approach, a new class of fluorinated poly(lactic-co-glycolic acid) co-polymers (F-PLGA) were designed that contain an increasing number of magnetically equivalent fluorine atoms. In particular, two novel compounds, F₃-PLGA and F₉-PLGA, were synthesized and their chemical structure and thermal stability were analyzed by solution NMR, DSC, and TGA. The obtained F-PLGA compounds were proven to form in aqueous solution colloidal stable nanoparticles (NPs) displaying a strong ¹⁹F NMR signal. The fluorinated NPs also showed an enhanced ability to load hydrophobic drugs containing fluorine atoms compared to analogous pristine PLGA NPs. Preliminary in vitro studies showed high cell viability and the NP ability to intracellularly deliver and release a functioning drug.