Exotic Heavy Quarkonium Spectroscopy: A Mini-review

Since nine years experiments have been observing a host of exotic states decaying into heavy quarkonia. The interpretation of most of them still remains uncertain and, in some cases, controversial, notwithstanding a considerable progress has been made on the quality of the experimental information available and a number of ideas and models have been put forward to explain the observations. In this mini-review we will summarize the measurements, with the most recent updates, and list the useful ones yet to be done. We will discuss the problem of the spin of the X, which could hide some major surprise on its interpretation, and review some more phenomenological issues debated in the field.Comment: 14 pages, 2 figures, 5 tables. To appear in Mod. Phys. Lett.

Anytime coalition structure generation on synergy graphs

We consider the coalition structure generation (CSG) problem on synergy graphs, which arises in many practical applications where communication constraints, social or trust relationships must be taken into account when forming coalitions. We propose a novel representation of this problem based on the concept of edge contraction, and an innovative branch and bound approach (CFSS), which is particularly efficient when applied to a general class of characteristic functions. This new model provides a non-redundant partition of the search space, hence allowing an effective parallelisation. We evaluate CFSS on two benchmark functions, the edge sum with coordination cost and the collective energy purchasing functions, comparing its performance with the best algorithm for CSG on synergy graphs: DyCE. The latter approach is centralised and cannot be efficiently parallelised due to the exponential memory requirements in the number of agents, which limits its scalability (while CFSS memory requirements are only polynomial). Our results show that, when the graphs are very sparse, CFSS is 4 orders of magnitude faster than DyCE. Moreover, CFSS is the first approach to provide anytime approximate solutions with quality guarantees for very large systems (i.e., with more than 2700 agents

Collective oscillations in disordered neural networks

We investigate the onset of collective oscillations in a network of pulse-coupled leaky-integrate-and-fire neurons in the presence of quenched and annealed disorder. We find that the disorder induces a weak form of chaos that is analogous to that arising in the Kuramoto model for a finite number N of oscillators [O.V. Popovych at al., Phys. Rev. E 71} 065201(R) (2005)]. In fact, the maximum Lyapunov exponent turns out to scale to zero for N going to infinite, with an exponent that is different for the two types of disorder. In the thermodynamic limit, the random-network dynamics reduces to that of a fully homogenous system with a suitably scaled coupling strength. Moreover, we show that the Lyapunov spectrum of the periodically collective state scales to zero as 1/N^2, analogously to the scaling found for the `splay state'.Comment: 8.5 Pages, 12 figures, submitted to Physical Review

Entropy potential and Lyapunov exponents

According to a previous conjecture, spatial and temporal Lyapunov exponents of chaotic extended systems can be obtained from derivatives of a suitable function: the entropy potential. The validity and the consequences of this hypothesis are explored in detail. The numerical investigation of a continuous-time model provides a further confirmation to the existence of the entropy potential. Furthermore, it is shown that the knowledge of the entropy potential allows determining also Lyapunov spectra in general reference frames where the time-like and space-like axes point along generic directions in the space-time plane. Finally, the existence of an entropy potential implies that the integrated density of positive exponents (Kolmogorov-Sinai entropy) is independent of the chosen reference frame.Comment: 20 pages, latex, 8 figures, submitted to CHAO

Doubly Heavy Tetraquarks in the Born-Oppenheimer approximation

Tetraquarks Q Q qbar qbar are found to be described remarkably well with the Quantum Chromodynamics version of the Hydrogen bond, as treated with the Born-Oppenheimer approximation. We show the robustness of the method by computing the mass of the observed T_cc tetraquark following two different paths. Relying on this, we provide a prediction for the mass of the expected T_bb particle.Comment: 8 pages, 1 figur

A simple and efficient statistical potential for scoring ensembles of protein structures

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Four-Quark Hadrons: an Updated Review

The past decade witnessed a remarkable proliferation of exotic charmonium-like resonances discovered at accelerators. In particular, the recently observed charged states are clearly not interpretable as q-qbar mesons. Notwithstanding the considerable advances on the experimental side, conflicting theoretical descriptions do not seem to provide a definitive picture about the nature of the so-called XYZ particles. We present here a comprehensive review about this intriguing topic, discussing both those experimental and theoretical aspects which we consider relevant to make further progress in the field. At this state of progress, XYZ phenomenology speaks in favour of the existence of compact four-quark particles (tetraquarks) and we believe that realizing this instructs us in the quest for a firm theoretical framework.Comment: 120 pages, 53 figures. Several typos corrected and some refs. added in v

Molecular analysis of sarcomeric and non-sarcomeric genes in patients with hypertrophic cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is a common genetic heart disorder characterized by unexplained left ventricle hypertrophy associated with non-dilated ventricular chambers. Several genes encoding heart sarcomeric proteins have been associated to HCM, but a small proportion of HCM patients harbor alterations in other non-sarcomeric loci. The variable expression of HCM seems influenced by genetic modifier factors and new sequencing technologies are redefining the understanding of genotype–phenotype relationships, even if the interpretations of the numerous identified variants pose several challenges. Methods and results: We investigated 62 sarcomeric and non-sarcomeric genes in 41 HCM cases and in 3 HCM-related disorders patients. We employed an integrated approach that combines multiple tools for the prediction, annotation and visualization of functional variants. Genotype–phenotype correlations were carried out for inspecting the involvement of each gene in age onset and clinical variability of HCM. The 80% of the non-syndromic patients showed at least one rare non-synonymous variant (nsSNV) and among them, 58% carried alterations in sarcomeric loci, 14% in desmosomal and 7% in other non-sarcomeric ones without any sarcomere change. Statistical analyses revealed an inverse correlation between the number of nsSNVs and age at onset, and a relationship between the clinical variability and number and type of variants. Conclusions: Our results extend the mutational spectrum of HCM and contribute in defining the molecular pathogenesis and inheritance pattern(s) of this condition. Besides, we delineate a specific procedure for the identification of the most likely pathogenetic variants for a next generation sequencing approach embodied in a clinical context

Technological and Economic Optimization of Functional Ready to Eat Meal

A ready meal based on precooked gluten-free pasta with a yogurt-based sauce enriched with probiotic bacteria was developed and optimized from both the nutritional and sensory point of view. Conceptually, the work aims at understanding the innovation stress in consumers and check whether the “perfect beauty” of a complex food product innovation, which is extremely admirable from a food technology point of view, could be effectively appreciated by consumers. In other words, we are interested in knowing whether there exists a gap between science-based or ”innovation-leading” technologists’ food preferences and consumers’ preferences, which are taste, information, price and promotion driven

Rate maintenance and resonance in the entorhinal cortex

Throughout the brain, neurons encode information in fundamental units of spikes. Each spike represents the combined thresholding of synaptic inputs and intrinsic neuronal dynamics. Here, we address a basic question of spike train formation: how do perithreshold synaptic inputs perturb the output of a spiking neuron? We recorded from single entorhinal principal cells in vitro and drove them to spike steadily at ∼5 Hz (theta range) with direct current injection, then used a dynamic-clamp to superimpose strong excitatory conductance inputs at varying rates. Neurons spiked most reliably when the input rate matched the intrinsic neuronal firing rate. We also found a striking tendency of neurons to preserve their rates and coefficients of variation, independently of input rates. As mechanisms for this rate maintenance, we show that the efficacy of the conductance inputs varied with the relationship of input rate to neuronal firing rate, and with the arrival time of the input within the natural period. Using a novel method of spike classification, we developed a minimal Markov model that reproduced the measured statistics of the output spike trains and thus allowed us to identify and compare contributions to the rate maintenance and resonance. We suggest that the strength of rate maintenance may be used as a new categorization scheme for neuronal response and note that individual intrinsic spiking mechanisms may play a significant role in forming the rhythmic spike trains of activated neurons; in the entorhinal cortex, individual pacemakers may dominate production of the regional theta rhythm