Computer Aided Aroma Design. I. Molecular knowledge framework

Computer Aided Aroma Design (CAAD) is likely to become a hot issue as the REACH EC document targets many aroma compounds to require substitution. The two crucial steps in CAMD are the generation of candidate molecules and the estimation of properties, which can be difficult when complex molecular structures like odours are sought and when their odour quality are definitely subjective whereas their odour intensity are partly subjective as stated in Rossitier’s review (1996). In part I, provided that classification rules like those presented in part II exist to assess the odour quality, the CAAD methodology presented proceeds with a multilevel approach matched by a versatile and novel molecular framework. It can distinguish the infinitesimal chemical structure differences, like in isomers, that are responsible for different odour quality and intensity. Besides, its chemical graph concepts are well suited for genetic algorithm sampling techniques used for an efficient screening of large molecules such as aroma. Finally, an input/output XML format based on the aggregation of CML and ThermoML enables to store the molecular classes but also any subjective or objective property values computed during the CAAD process

Computer Aided Aroma Design. II. Quantitative structure-odour relationship

Computer Aided Aroma Design (CAAD) is likely to become a hot issue as the REACH EC document targets many aroma compounds to require substitution. The two crucial steps in CAMD are the generation of candidate molecules and the estimation of properties, which can be difficult when complex molecular structures like odours are sought and their odour quality are definitely subjective or their odour intensity are partly subjective as stated in Rossitier’s review (1996). The CAAD methodology and a novel molecular framework were presented in part I. Part II focuses on a classification methodology to characterize the odour quality of molecules based on Structure – Odour Relation (SOR). Using 2D and 3D molecular descriptors, Linear Discriminant Analysis (LDA) and Artificial Neural Network are compared in favour of LDA. The classification into balsamic / non balsamic quality was satisfactorily solved. The classification among five sub notes of the balsamic quality was less successful, partly due to the selection of the Aldrich’s Catalog as the reference classification. For the second case, it is shown that the sweet sub note considered in Aldrich’s Catalog is not a relevant sub note, confirming the alternative and popular classification of Jaubert et al., (1995), the field of odours

Vibration Induced Non-adiabatic Geometric Phase and Energy Uncertainty of Fermions in Graphene

We investigate geometric phase of fermion states under relative vibrations of two sublattices in graphene by solving time-dependent Sch\"{o}dinger equation using Floquet scheme. In a period of vibration the fermions acquire different geometric phases depending on their momenta. There are two regions in the momentum space: the adiabatic region where the geometric phase can be approximated by the Berry phase and the chaotic region where the geometric phase drastically fluctuates in changing parameters. The energy of fermions due to vibrations shows spikes in the chaotic region. The results suggest a possible dephasing mechanism which may cause classical-like transport properties in graphene.Comment: 9 pages, 5 figure

State of knowledge of methodologies for establishing “typologies of production systems”

In sub-Saharan Africa, climatic hazards and land pressure have stimulated a search for production intensification methods, adapted to the various environments and types of farming, in a bid to ensure food security in the region. Indeed, this intensification is conditioned by the availability to farmers of innovations that are adapted to their constraints and priorities. Thus, the adaptation of innovations to the diversity of agricultural production systems requires establishment of typologies that reflect the heterogeneity of farms and make it possible to reduce diversity to a manageable scale. In this article, we reviewed the state of knowledge on methods for establishing “typologies of production systems”, based on existing knowledge, in order to examine the extent to which they enable understanding of this reality of the agricultural economy. Faced with current global challenges, such as population growth and climate change, sufficient food supplies and quality will require more efficient and robust production systems, based on good agricultural practices that ensure efficient use of the natural resource base, and within an enabling policy and institutional environment. Improving production systems for sustainability will, therefore, need to be based on the implementation of relevant recommendations derived from typologies built through science-based robust methodology, combining participatory approaches and quantitative and qualitative data analysis methods, “data mining”. &nbsp

Rigorous derivation of coherent resonant tunneling time and velocity in finite periodic systems

The velocity $v_{res}$ of resonant tunneling electrons in finite periodic structures is analytically calculated in two ways. The first method is based on the fact that a transmission of unity leads to a coincidence of all still competing tunneling time definitions. Thus, having an indisputable resonant tunneling time $\tau_{res},$ we apply the natural definition $v_{res}=L/\tau_{res}$ to calculate the velocity. For the second method we combine Bloch's theorem with the transfer matrix approach to decompose the wave function into two Bloch waves. Then the expectation value of the velocity is calculated. Both different approaches lead to the same result, showing their physical equivalence. The obtained resonant tunneling velocity $v_{res}$ is smaller or equal to the group velocity times the magnitude of the complex transmission amplitude of the unit cell. Only at energies where the unit cell of the periodic structure has a transmission of unity $v_{res}$ equals the group velocity. Numerical calculations for a GaAs/AlGaAs superlattice are performed. For typical parameters the resonant velocity is below one third of the group velocity.Comment: 12 pages, 3 figures, LaTe