Effect of the Structure of Amido-polynitrogen Molecules on the Complexation of Actinides

AbstractThe complexation and solvent extraction of Eu(III) and actinides in different oxidation states (Am(III), Pu(IV), Np(V)) by bitopic molecules with a dipyridyl-phenanthroline cycle as nitrogen unit and one or two amido functions are described. The complexation has been studied in methanol-water solution with hydrophilic molecules to enhance knowledge about this new family of ligands and to identify the most interesting structural effect. Some extraction tests have been performed with lipophilic molecules of the family to check the possible utility of the new class of ligands under representative fuel reprocessing conditions. These first studies have demonstrated that the presence of a preorganized N-donors unit like dipyridyl-phenanthroline improves the ligand's affinity for actinides and its An/Ln selectivity

Head and neck target delineation using a novel PET automatic segmentation algorithm

Purpose To evaluate the feasibility and impact of using a novel advanced PET auto-segmentation method in Head and Neck (H&N) radiotherapy treatment (RT) planning. Methods ATLAAS, Automatic decision Tree-based Learning Algorithm for Advanced Segmentation, previously developed and validated on pre-clinical data, was applied to 18F-FDG-PET/CT scans of 20 H&N patients undergoing Intensity Modulated Radiation Therapy. Primary Gross Tumour Volumes (GTVs) manually delineated on CT/MRI scans (GTVpCT/MRI), together with ATLAAS-generated contours (GTVpATLAAS) were used to derive the RT planning GTV (GTVpfinal). ATLAAS outlines were compared to CT/MRI and final GTVs qualitatively and quantitatively using a conformity metric. Results The ATLAAS contours were found to be reliable and useful. The volume of GTVpATLAAS was smaller than GTVpCT/MRI in 70% of the cases, with an average conformity index of 0.70. The information provided by ATLAAS was used to grow the GTVpCT/MRI in 10 cases (up to 10.6 mL) and to shrink the GTVpCT/MRI in 7 cases (up to 12.3 mL). ATLAAS provided complementary information to CT/MRI and GTVpATLAAS contributed to up to 33% of the final GTV volume across the patient cohort. Conclusions ATLAAS can deliver operator independent PET segmentation to augment clinical outlining using CT and MRI and could have utility in future clinical studies

Simulations of protostellar collapse using multigroup radiation hydrodynamics. I. The first collapse

Radiative transfer plays a major role in the process of star formation. Many simulations of gravitational collapse of a cold gas cloud followed by the formation of a protostellar core use a grey treatment of radiative transfer coupled to the hydrodynamics. However, dust opacities which dominate extinction show large variations as a function of frequency. In this paper, we used frequency-dependent radiative transfer to investigate the influence of the opacity variations on the properties of Larson's first core. We used a multigroup M1 moment model in a 1D radiation hydrodynamics code to simulate the spherically symmetric collapse of a 1 solar mass cloud core. Monochromatic dust opacities for five different temperature ranges were used to compute Planck and Rosseland means inside each frequency group. The results are very consistent with previous studies and only small differences were observed between the grey and multigroup simulations. For a same central density, the multigroup simulations tend to produce first cores with a slightly higher radius and central temperature. We also performed simulations of the collapse of a 10 and 0.1 solar mass cloud, which showed the properties of the first core to be independent of the initial cloud mass, with again no major differences between grey and multigroup models. For Larson's first collapse, where temperatures remain below 2000 K, the vast majority of the radiation energy lies in the IR regime and the system is optically thick. In this regime, the grey approximation does a good job reproducing the correct opacities, as long as there are no large opacity variations on scales much smaller than the width of the Planck function. The multigroup method is however expected to yield more important differences in the later stages of the collapse when high energy (UV and X-ray) radiation is present and matter and radiation are strongly decoupled.Comment: 9 pages, 5 figures, accepted for publication in A&

Alternating Tree Automata with Qualitative Semantics

We study alternating automata with qualitative semantics over infinite binary trees: Alternation means that two opposing players construct a decoration of the input tree called a run, and the qualitative semantics says that a run of the automaton is accepting if almost all branches of the run are accepting. In this article, we prove a positive and a negative result for the emptiness problem of alternating automata with qualitative semantics. The positive result is the decidability of the emptiness problem for the case of Büchi acceptance condition. An interesting aspect of our approach is that we do not extend the classical solution for solving the emptiness problem of alternating automata, which first constructs an equivalent non-deterministic automaton. Instead, we directly construct an emptiness game making use of imperfect information. The negative result is the undecidability of the emptiness problem for the case of co-Büchi acceptance condition. This result has two direct consequences: The undecidability of monadic second-order logic extended with the qualitative path-measure quantifier and the undecidability of the emptiness problem for alternating tree automata with non-zero semantics, a recently introduced probabilistic model of alternating tree automata

Comparison of machine learning algorithms in restaurant revenue prediction

In this paper, we address several aspects of applying classical machine learning algorithms to a regression problem. We compare the predictive power to validate our approach on a data about revenue of a large Russian restaurant chain. We pay special attention to solve two problems: data heterogeneity and a high number of correlated features. We describe methods for considering heterogeneity—observations weighting and estimating models on subsamples. We define a weighting function via Mahalanobis distance in the space of features and show its predictive properties on following methods: ordinary least squares regression, elastic net, support vector regression, and random forest.</p

Considerations for the design and conduct of human gut microbiota intervention studies relating to foods

With the growing appreciation for the influence of the intestinal microbiota on human health, there is increasing motivation to design and refine interventions to promote favorable shifts in the microbiota and their interactions with the host. Technological advances have improved our understanding and ability to measure this indigenous population and the impact of such interventions. However, the rapid growth and evolution of the field, as well as the diversity of methods used, parameters measured and populations studied, make it difficult to interpret the significance of the findings and translate their outcomes to the wider population. This can prevent comparisons across studies and hinder the drawing of appropriate conclusions. This review outlines considerations to facilitate the design, implementation and interpretation of human gut microbiota intervention studies relating to foods based upon our current understanding of the intestinal microbiota, its functionality and interactions with the human host. This includes parameters associated with study design, eligibility criteria, statistical considerations, characterization of products and the measurement of compliance. Methodologies and markers to assess compositional and functional changes in the microbiota, following interventions are discussed in addition to approaches to assess changes in microbiota–host interactions and host responses. Last, EU legislative aspects in relation to foods and health claims are presented. While it is appreciated that the field of gastrointestinal microbiology is rapidly evolving, such guidance will assist in the design and interpretation of human gut microbiota interventional studies relating to foods

Designing Luxury Experience

In luxury brand management, experiences are essential. However, most of what we know about designing customer experiences originates from work developed with and/or for mass brands. Luxury brands are conceptually different and require a specific approach to brand management. Using a grounded theory approach, we present a framework consisting of seven principles to design luxury experience. Our research suggests that to create a true luxury experience brands should go beyond traditional frameworks of brand management. By compiling best practices and the commonalities amongst the interviewed companies' most successful efforts to create a luxury experience, the framework can help brands to implement a trading-up strategy: Luxury brands can enhance their desirability by offering a true luxury experience and non-luxury brands can adopt principles of luxury experience and become life-style brands

Dilepton production in heavy ion collisions at intermediate energies

We present a unified description of the vector meson and dilepton production in elementary and in heavy ion reactions. The production of vector mesons ($\rho,\omega$) is described via the excitation of nuclear resonances ($R$). The theoretical framework is an extended vector meson dominance model (eVMD). The treatment of the resonance decays $R\longmapsto NV$ with arbitrary spin is covariant and kinematically complete. The eVMD includes thereby excited vector meson states in the transition form factors. This ensures correct asymptotics and provides a unified description of photonic and mesonic decays. The resonance model is successfully applied to the $\omega$ production in $p+p$ reactions. The same model is applied to the dilepton production in elementary reactions ($p+p, p+d$). Corresponding data are well reproduced. However, when the model is applied to heavy ion reactions in the BEVALAC/SIS energy range the experimental dilepton spectra measured by the DLS Collaboration are significantly underestimated at small invariant masses. As a possible solution of this problem the destruction of quantum interference in a dense medium is discussed. A decoherent emission through vector mesons decays enhances the corresponding dilepton yield in heavy ion reactions. In the vicinity of the $\rho/\omega$-peak the reproduction of the data requires further a substantial collisional broadening of the $\rho$ and in particular of the $\omega$ meson.Comment: 32 pages revtex, 19 figures, to appear in PR