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

Learning a local symmetry with neural networks

We explore the capacity of neural networks to detect a symmetry with complex local and non-local patterns: the gauge symmetry Z2. This symmetry is present in physical problems from topological transitions to quantum chromodynamics, and controls the computational hardness of instances of spin-glasses. Here, we show how to design a neural network, and a dataset, able to learn this symmetry and to find compressed latent representations of the gauge orbits. Our method pays special attention to system-wrapping loops, the so-called Polyakov loops, known to be particularly relevant for computational complexity

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

Spatial correlations in attribute communities

Community detection is an important tool for exploring and classifying the properties of large complex networks and should be of great help for spatial networks. Indeed, in addition to their location, nodes in spatial networks can have attributes such as the language for individuals, or any other socio-economical feature that we would like to identify in communities. We discuss in this paper a crucial aspect which was not considered in previous studies which is the possible existence of correlations between space and attributes. Introducing a simple toy model in which both space and node attributes are considered, we discuss the effect of space-attribute correlations on the results of various community detection methods proposed for spatial networks in this paper and in previous studies. When space is irrelevant, our model is equivalent to the stochastic block model which has been shown to display a detectability-non detectability transition. In the regime where space dominates the link formation process, most methods can fail to recover the communities, an effect which is particularly marked when space-attributes correlations are strong. In this latter case, community detection methods which remove the spatial component of the network can miss a large part of the community structure and can lead to incorrect results.Comment: 10 pages and 7 figure

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

Morphological bases of phytoplankton energy management and physiological responses unveiled by 3D subcellular imaging

Eukaryotic phytoplankton have a small global biomass but play major roles in primary production and climate. Despite improved understanding of phytoplankton diversity and evolution, we largely ignore the cellular bases of their environmental plasticity. By comparative 3D morphometric analysis across seven distant phytoplankton taxa, we observe constant volume occupancy by the main organelles and preserved volumetric ratios between plastids and mitochondria. We hypothesise that phytoplankton subcellular topology is modulated by energy-management constraints. Consistent with this, shifting the diatom Phaeodactylum from low to high light enhances photosynthesis and respiration, increases cell-volume occupancy by mitochondria and the plastid CO2-fixing pyrenoid, and boosts plastid mitochondria contacts. Changes in organelle architectures and interactions also accompany Nannochloropsis acclimation to different trophic lifestyles, along with respiratory and photosynthetic responses. By revealing evolutionarily-conserved topologies of energy-managing organelles, and their role in phytoplankton acclimation, this work deciphers phytoplankton responses at subcellular scales

Effect of simulated microgravity on the virulence properties of the opportunistic bacterial pathogen Staphylococcus aureus

Extended manned space flight will result in a diminution of immune status and cause profound changes in the human bacterial microbiota, leading to increased risk of infection. Experiments conducted during short-term flight suggest that growth in microgravity leads to increases in bacterial antibiotic resistance and to cell wall changes. Growth under low-shear modelled microgravity (LSMMG) indicated that a reduced gravitational field acts as an environmental signal for expression of enhanced bacterial virulence in Gram-negative pathogens. We examined the effect of simulated microgravity on parameters of virulence in clinical isolates of Staphylococcus aureus. Three strains were grown under LSMMG in a High Aspect Ratio Vessel and compared with cells grown under normal gravity (NG) in the same vessel. There were no significant differences in the antibiotic susceptibility, growth rate or morphology of staphylococci grown under LSMMG compared to NG. LSMMG-induced reductions in synthesis of the pigment staphyloxanthin were noted. Strains secreted less protein under LSMMG and reductions in haemolysin secretion were found. Reduced expression of the major virulence determinant "-toxin in the microgravity environment was found by gene amplification. Thus, in contrast to published data on Gram-negative pathogens, simulated microgravity reduces the expression of key virulence determinants of S. aureus

A "hair-raising" history of alopecia areata

YesA 3500‐year‐old papyrus from ancient Egypt provides a list of treatments for many diseases including “bite hair loss,” most likely alopecia areata (AA). The treatment of AA remained largely unchanged for over 1500 years. In 30 CE, Celsus described AA presenting as scalp alopecia in spots or the “windings of a snake” and suggested treatment with caustic compounds and scarification. The first “modern” description of AA came in 1813, though treatment still largely employed caustic agents. From the mid‐19th century onwards, various hypotheses of AA development were put forward including infectious microbes (1843), nerve defects (1858), physical trauma and psychological stress (1881), focal inflammation (1891), diseased teeth (1902), toxins (1912) and endocrine disorders (1913). The 1950s brought new treatment developments with the first use of corticosteroid compounds (1952), and the first suggestion that AA was an autoimmune disease (1958). Research progressively shifted towards identifying hair follicle‐specific autoantibodies (1995). The potential role of lymphocytes in AA was made implicit with immunohistological studies (1980s). However, studies confirming their functional role were not published until the development of rodent models (1990s). Genetic studies, particularly genome‐wide association studies, have now come to the forefront and open up a new era of AA investigation (2000s). Today, AA research is actively focused on genetics, the microbiome, dietary modulators, the role of atopy, immune cell types in AA pathogenesis, primary antigenic targets, mechanisms by which immune cells influence hair growth, and of course the development of new treatments based on these discoveries.Alopecia UK