Analysis of flow cytometric aneuploid DNA histograms: validation of an automatic procedure against ad hoc experimental data

In this paper we present an improved version of a method for the automatic analysis of flow cytometric DNA histograms from samples containing a mixture of two cell populations. The procedure is tested against two sets of ad hoc experimental data, obtained by mixing cultures of cell lines in different known proportions. The potentialities of the method are enlightened and discussed with regard to its capability of recovering the population percentages, the DNA index and the G0/G1, S, G2+M phase fractions of each population. On the basis of the obtained results, the procedure appears to be a promising tool in the flow cytometric data analysis and, in particular, in problems of diagnosis and prognosis of tumor diseases

Ring Reservoir Neural Networks for Graphs

Machine Learning for graphs is nowadays a research topic of consolidated relevance. Common approaches in the field typically resort to complex deep neural network architectures and demanding training algorithms, highlighting the need for more efficient solutions. The class of Reservoir Computing (RC) models can play an important role in this context, enabling to develop fruitful graph embeddings through untrained recursive architectures. In this paper, we study progressive simplifications to the design strategy of RC neural networks for graphs. Our core proposal is based on shaping the organization of the hidden neurons to follow a ring topology. Experimental results on graph classification tasks indicate that ring-reservoirs architectures enable particularly effective network configurations, showing consistent advantages in terms of predictive performance

Reservoir Topology in Deep Echo State Networks

Deep Echo State Networks (DeepESNs) recently extended the applicability of Reservoir Computing (RC) methods towards the field of deep learning. In this paper we study the impact of constrained reservoir topologies in the architectural design of deep reservoirs, through numerical experiments on several RC benchmarks. The major outcome of our investigation is to show the remarkable effect, in terms of predictive performance gain, achieved by the synergy between a deep reservoir construction and a structured organization of the recurrent units in each layer. Our results also indicate that a particularly advantageous architectural setting is obtained in correspondence of DeepESNs where reservoir units are structured according to a permutation recurrent matrix

Gluon propagator, triple gluon vertex and the QCD coupling constant

We study the UV-scaling of the flavorless gluon propagator in the Landau gauge in an energy window up to 9 GeV. Dominant hypercubic lattice artifacts are eliminated. A large set of renormalization schemes is used to test asymptotic scaling. We compare with our results obtained directly from the triple gluon vertex. We end-up with \Lambda_{\bar{\rm{MS}}} = 318(12)(5) MeV and 292(5)(15) MeV respectively for these two methods, compatible which each other but significantly above the Schrodinger method estimate.Comment: 3 pages, LaTeX with two figures; presented at LATTICE9

KRb Feshbach Resonances: Modeling the interatomic potential

We have observed 28 heteronuclear Feshbach resonances in 10 spin combinations of the hyperfine ground states of a 40K 87Rb mixture. The measurements were performed by observing the loss rates from an atomic mixture at magnetic fields between 0 and 700 G. This data was used to significantly refine an interatomic potential derived from molecular spectroscopy, yielding a highly consistent model of the KRb interaction. Thus, the measured resonances can be assigned to the corresponding molecular states. In addition, this potential allows for an accurate calculation of the energy differences between highly excited levels and the rovibrational ground level. This information is of particular relevance for the formation of deeply bound heteronuclear molecules. Finally, the model is used to predict Feshbach resonances in mixtures of 87Rb combined with 39K or 41K.Comment: 4 pages, 3 figure

Lattice calculation of 1/p21/p^2 corrections to αs\alpha_s and of ΛQCD\Lambda_{\rm {QCD}} in the MOM~\widetilde{MOM} scheme

We report on very strong evidence of the occurrence of power terms in \as(p), the QCD running coupling constant in the $\widetilde{MOM}$ scheme, by analyzing non-perturbative measurements from the lattice three-gluon vertex between 2.0 and 10.0 GeV at zero flavor. While putting forward the caveat that this definition of the coupling is a gauge dependent one, the general relevance of such an occurrence is discussed. We fit $\Lambda_{\bar{\rm MS}}^{(n_f=0)}= 237 \pm 3 ^{+ 0}_{-10}$ MeV in perfect agreement with the result obtained by the ALPHA group with a totally different method. The power correction to \as(p) is fitted to $(0.63\pm 0.03 ^{+ 0.0}_{- 0.13}) {\rm GeV}^2/p^2$.Comment: 21 pages, 3 figure

Assessment of Posidonia oceanica (L.) Delile conservation status by standard and putative approaches: the case study of Santa Marinella meadow (Italy, W Mediterranean)

The conservation status of the Posidonia oceanica meadow at Santa Marinella (Rome) was evaluated through both standard (bed density, leaf biometry, "A" coefficient, Leaf Area Index, rhizome production) and biochemical/genetic approaches (total phenol content and Random Amplified Polymorphic DNA marker). The bio-chemical/genetic results are in agreement with those obtained by standard approaches. The bed under study was ranked as a disturbed one, due to its low density, and high heterogeneity in leaf biometry, LAI values, "A" coefficient and primary production. This low quality ranking is confirmed by both mean phenol content in plants, quite high and scattered, and by the low genetic variability in the meadow, with a very high similarity of specimen at a local scale. Hence, these two putative approaches clearly identify the endangered conservation status of the meadow. They link plant biodiversity and ecophysiology to ecosystem 'health'. Furthermore, they are repeatable and standardizable and could be usefully introduced in meadows monitoring to check environmental quality