3-D structural modeling of humic acids through experimental characterization,computer assisted structure elucidation and atomistic simulations. 1. Chelsea soil humic acid

This paper describes an integrated experimental and computational framework for developing 3-D structural models for humic acids (HAs). This approach combines experimental characterization, computer assisted structure elucidation (CASE), and atomistic simulations to generate all 3-D structural models or a representative sample of these models consistent with the analytical data and bulk thermodynamic/structural properties of HAs. To illustrate this methodology, structural data derived from elemental analysis, diffuse reflectance FT-IR spectroscopy, 1-D/2-D 1H and 13C solution NMR spectroscopy, and electrospray ionization quadrupole time-of-flight mass spectrometry (ESI QqTOF MS) are employed as input to the CASE program SIGNATURE to generate all 3-D structural models for Chelsea soil humic acid (HA). These models are subsequently used as starting 3-D structures to carry out constant temperature-constant pressure molecular dynamics simulations to estimate their bulk densities and Hildebrand solubility parameters. Surprisingly, only a few model isomers are found to exhibit molecular compositions and bulk thermodynamic properties consistent with the experimental data. The simulated 13C NMR spectrum of an equimolar mixture of these model isomers compares favorably with the measured spectrum of Chelsea soil HA.     

Study of mass transfer and determination of drop size distribution in a pulsed extraction column

A better understanding of pulsed liquid-liquid extraction columns was obtained by using an online digital image analysis system to characterize emulsion drop. The mass transfer of acetic acid from dispersed phase (ethyl acetate) to continuous phase (water) was studied under standard conditions. The system enabled drop size distribution (DSD) to be measured as a function of physical and thermodynamic parameters. The surface tension was investigated by static contact angle measurement. Mass transfer and energy transfer, characterized by the surface/volume ratio of the droplets were compared with the working parameters in order to interpret restrictive phenomena such as hold up and column efficiency. The experimental values of Sauter diameter (d₃₂) and those predicted by a correlation proposed in the literature are in good agreement. However, the adhesion work between liquid and PTFE plate surface indicates that interface property variations, as a function of solute concentration, must be taken into account in the theoretical correlations. It was found that hold up and separation efficiency depend mainly on the stirring rate. These results show that online image analysis can be used as a process control of a liquid-liquid extraction column in order to optimize the mixing phenomena and the DSD, the key parameter of extraction efficiency.     

Depth resolution and multiexponential lifetime analyses of reflectance-based time-domain fluorescence data

Time-domain fluorescence imaging is a powerful new technique that adds a rich amount of information to conventional fluorescence imaging. Specifically, time-domain fluorescence can be used to remove autofluorescence from signals, resolve multiple fluorophore concentrations, provide information about tissue microenvironments, and, for reflectance-based imaging systems, resolve inclusion depth. The present study provides the theory behind an improved method of analyzing reflectance-based time-domain data that is capable of accurately recovering mixed concentration ratios of multiple fluorescent agents while also recovering the depth of the inclusion. The utility of the approach was demonstrated in a number of simulations and in tissuelike phantom experiments using a short source-detector separation system. The major findings of this study were (1) both depth of an inclusion and accurate ratios of two-fluorophore concentrations can be recovered accurately up to depths of approximately 1 cm with only the optical properties of the medium as prior knowledge, (2) resolving the depth and accounting for the dispersion effects on fluorescent lifetimes is crucial to the accuracy of recovered ratios, and (3) ratios of three-fluorophore concentrations can be resolved at depth but only if the lifetimes of the three fluorophores are used as prior knowledge. By accurately resolving the concentration ratios of two to three fluorophores, it may be possible to remove autofluorescence or carry out quantitative techniques, such as reference tracer kinetic modeling or ratiometric approaches, to determine receptor binding or microenvironment parameters in point-based time-domain fluorescence applications.     

Novel nanostructured pHEMA-TiO2 hybrid materials with efficient light-induced charge separation

We report on a new approach to the fabrication of an electronic material: organic-inorganic pHEMA-oxo-TiO(2) hybrid with efficient light-induced separation of charges. Particular attention is paid to the material nanoscale morphology. The size-selected 5.0 nm titanium oxo-alkoxy nanoparticles are prepared in a sol-gel reactor with rapid (turbulent) fluid micromixing and the ligand exchange results in a stable nanoparticulate precursor in HEMA solution, in which polymerization can be induced thermally or by photons. The obtained hybrid materials demonstrate the highest quantum yield of photoinduced charge separation of 50% and can store photoinduced electrons at a number density above 10% Ti atoms.     

I4EU (Industry 4.0 for European Union) ——An European Initiative to Develop Training Activity

This paper presents an on-going European ERASMUS project to develop training programs and tools for Industry 4.0. After an introduction on the background and objective of the project, the paper will give an overview on the structure, partners and organization of the project. Based on the State-of-the-art, the targeted intellectual outputs (IOs) will be presented in detail and the set of planned activities to achieve IOs are outlined. The project progress and preliminary results are shown and the concluding summary will be given at the end of the paper.     

The State of the Art in Agent Communication Languages

Like societies of humans, there is a need for agents in a multi-agent system to rely on one another, enlist the support of peers in order to solve complex tasks. Agents will be able to cooperate only through a meaningful communication language that can bear correctly their mental states and convey precisely the content of their messages. In search for the ideal agent communication language (ACL), several initiatives like the pioneering work of the Knowledge Sharing Effort and the Foundation for Intelligent Physical Agents (FIPA) are paving the way for a platform where all agents would be able to interact regardless of their implementation environment. ACL is a new field of study that could gain from a survey in expanding its application areas. For this purpose, we examine in this paper the state of the art in ACL design and suggest some principles for building a generalized ACL framework. We then evaluate some existing ACL models, and present the current issues in ACL research, and new perspectives. Received 22 July 1999 / Revised 23 March 2000 / Accepted 2 May 2000     

Efficient approaches for ℓ2-ℓ0 regularization and applications to feature selection in SVM

For solving a class of ?₂- ?₀- regularized problems we convexify the nonconvex ?₂- ?₀ term with the help of its biconjugate function. The resulting convex program is explicitly given which possesses a very simple structure and can be handled by convex optimization tools and standard softwares. Furthermore, to exploit simultaneously the advantage of convex and nonconvex approximation approaches, we propose a two phases algorithm in which the convex relaxation is used for the first phase and in the second phase an efficient DCA (Difference of Convex functions Algorithm) based algorithm is performed from the solution given by Phase 1. Applications in the context of feature selection in support vector machine learning are presented with experiments on several synthetic and real-world datasets. Comparative numerical results with standard algorithms show the efficiency the potential of the proposed approaches.