Cycle-based Cluster Variational Method for Direct and Inverse Inference

We elaborate on the idea that loop corrections to belief propagation could be dealt with in a systematic way on pairwise Markov random fields, by using the elements of a cycle basis to define region in a generalized belief propagation setting. The region graph is specified in such a way as to avoid dual loops as much as possible, by discarding redundant Lagrange multipliers, in order to facilitate the convergence, while avoiding instabilities associated to minimal factor graph construction. We end up with a two-level algorithm, where a belief propagation algorithm is run alternatively at the level of each cycle and at the inter-region level. The inverse problem of finding the couplings of a Markov random field from empirical covariances can be addressed region wise. It turns out that this can be done efficiently in particular in the Ising context, where fixed point equations can be derived along with a one-parameter log likelihood function to minimize. Numerical experiments confirm the effectiveness of these considerations both for the direct and inverse MRF inference.Comment: 47 pages, 16 figure

Propagation of Magnetic Avalanches in Mn12Ac at High Field Sweep Rates

Time-resolved measurements of the magnetization reversal in single crystals of Mn 12 Ac in pulsed magnetic fields, at magnetic field sweep rates from 1.5     kT / s up to 7     kT / s , suggest a new process that cannot be scaled onto a deflagrationlike propagation driven by heat diffusion. The sweep rate dependence of the propagation velocity, increasing from a few 100     m / s up to the speed of sound in Mn 12 Ac , indicates the existence of two new regimes at the highest sweep rates, with a transition around 4     kT / s that can be understood as a magnetic deflagration-to-detonation transition

Finite-size scaling analysis of the distributions of pseudo-critical temperatures in spin glasses

Using the results of large scale numerical simulations we study the probability distribution of the pseudo critical temperature for the three-dimensional Edwards-Anderson Ising spin glass and for the fully connected Sherrington-Kirkpatrick model. We find that the behavior of our data is nicely described by straightforward finite-size scaling relations.Comment: 23 pages, 9 figures. Version accepted for publication in J. Stat. Mec

Real space Renormalization Group analysis of a non-mean field spin-glass

A real space Renormalization Group approach is presented for a non-mean field spin-glass. This approach has been conceived in the effort to develop an alternative method to the Renormalization Group approaches based on the replica method. Indeed, non-perturbative effects in the latter are quite generally out of control, in such a way that these approaches are non-predictive. On the contrary, we show that the real space method developed in this work yields precise predictions for the critical behavior and exponents of the model

A review of approaches to supply chain communications: from manufacturing to construction

With the increasing importance of computer-based communication technologies, communication networks are becoming crucial in supply chain management. Given the objectives of the supply chain: to have the right products in the right quantities, at the right place, at the right moment and at minimal cost, supply chain management is situated at the intersection of different professional sectors. This is particularly the case in construction, since building needs for its fabrication the incorporation of a number of industrial products. This paper provides a review of the main approaches to supply chain communications as used mainly in manufacturing industries. The paper analyses the extent to which these have been applied to construction. It also reviews the on-going developments and research activities in this domain

3D City Models and urban information: Current issues and perspectives

Considering sustainable development of cities implies investigating cities in a holistic way taking into account many interrelations between various urban or environmental issues. 3D city models are increasingly used in different cities and countries for an intended wide range of applications beyond mere visualization. Could these 3D City models be used to integrate urban and environmental knowledge? How could they be improved to fulfill such role? We believe that enriching the semantics of current 3D city models, would extend their functionality and usability; therefore, they could serve as integration platforms of the knowledge related to urban and environmental issues allowing a huge and significant improvement of city sustainable management and development. But which elements need to be added to 3D city models? What are the most efficient ways to realize such improvement / enrichment? How to evaluate the usability of these improved 3D city models? These were the questions tackled by the COST Action TU0801 “Semantic enrichment of 3D city models for sustainable urban development”. This book gathers various materials developed all along the four year of the Action and the significant breakthroughs

Router-level community structure of the Internet Autonomous Systems

The Internet is composed of routing devices connected between them and organized into independent administrative entities: the Autonomous Systems. The existence of different types of Autonomous Systems (like large connectivity providers, Internet Service Providers or universities) together with geographical and economical constraints, turns the Internet into a complex modular and hierarchical network. This organization is reflected in many properties of the Internet topology, like its high degree of clustering and its robustness. In this work, we study the modular structure of the Internet router-level graph in order to assess to what extent the Autonomous Systems satisfy some of the known notions of community structure. We show that the modular structure of the Internet is much richer than what can be captured by the current community detection methods, which are severely affected by resolution limits and by the heterogeneity of the Autonomous Systems. Here we overcome this issue by using a multiresolution detection algorithm combined with a small sample of nodes. We also discuss recent work on community structure in the light of our results

Progressive and biased divergent evolution underpins the origin and diversification of peridinin dinoflagellate plastids

Dinoflagellates are algae of tremendous importance to ecosystems and to public health. The cell biology and genome organization of dinoflagellate species is highly unusual. For example, the plastid genomes of peridinin-containing dinoflagellates encode only a minimal number of genes arranged on small elements termed "minicircles". Previous studies of peridinin plastid genes have found evidence for divergent sequence evolution, including extensive substitutions, novel insertions and deletions, and use of alternative translation initiation codons. Understanding the extent of this divergent evolution has been hampered by the lack of characterized peridinin plastid sequences. We have identified over 300 previously unannotated peridinin plastid mRNAs from published transcriptome projects, vastly increasing the number of sequences available. Using these data, we have produced a well-resolved phylogeny of peridinin plastid lineages, which uncovers several novel relationships within the dinoflagellates. This enables us to define changes to plastid sequences that occurred early in dinoflagellate evolution, and that have contributed to the subsequent diversification of individual dinoflagellate clades. We find that the origin of the peridinin dinoflagellates was specifically accompanied by elevations both in the overall number of substitutions that occurred on plastid sequences, and in the Ka/Ks ratio associated with plastid sequences, consistent with changes in selective pressure. These substitutions, alongside other changes, have accumulated progressively in individual peridinin plastid lineages. Throughout our entire dataset, we identify a persistent bias toward non-synonymous substitutions occurring on sequences encoding photosystem I subunits and stromal regions of peridinin plastid proteins, which may have underpinned the evolution of this unusual organelle.Wellcome Trus

Message Passing for Optimization and Control of Power Grid: Model of Distribution System with Redundancy

We use a power grid model with $M$ generators and $N$ consumption units to optimize the grid and its control. Each consumer demand is drawn from a predefined finite-size-support distribution, thus simulating the instantaneous load fluctuations. Each generator has a maximum power capability. A generator is not overloaded if the sum of the loads of consumers connected to a generator does not exceed its maximum production. In the standard grid each consumer is connected only to its designated generator, while we consider a more general organization of the grid allowing each consumer to select one generator depending on the load from a pre-defined consumer-dependent and sufficiently small set of generators which can all serve the load. The model grid is interconnected in a graph with loops, drawn from an ensemble of random bipartite graphs, while each allowed configuration of loaded links represent a set of graph covering trees. Losses, the reactive character of the grid and the transmission-level connections between generators (and many other details relevant to realistic power grid) are ignored in this proof-of-principles study. We focus on the asymptotic limit and we show that the interconnects allow significant expansion of the parameter domains for which the probability of a generator overload is asymptotically zero. Our construction explores the formal relation between the problem of grid optimization and the modern theory of sparse graphical models. We also design heuristic algorithms that achieve the asymptotically optimal selection of loaded links. We conclude discussing the ability of this approach to include other effects, such as a more realistic modeling of the power grid and related optimization and control algorithms.Comment: 10 page

Metrics matter in community detection

We present a critical evaluation of normalized mutual information (NMI) as an evaluation metric for community detection. NMI exaggerates the leximin method's performance on weak communities: Does leximin, in finding the trivial singletons clustering, truly outperform eight other community detection methods? Three NMI improvements from the literature are AMI, rrNMI, and cNMI. We show equivalences under relevant random models, and for evaluating community detection, we advise one-sided AMI under the $\mathbb{M}_{\mathrm{all}}$ model (all partitions of $n$ nodes). This work seeks (1) to start a conversation on robust measurements, and (2) to advocate evaluations which do not give "free lunch"