General duality for abelian-group-valued statistical-mechanics models

We introduce a general class of statistical-mechanics models, taking values in an abelian group, which includes examples of both spin and gauge models, both ordered and disordered. The model is described by a set of ``variables'' and a set of ``interactions''. A Gibbs factor is associated to each variable and to each interaction. We introduce a duality transformation for systems in this class. The duality exchanges the abelian group with its dual, the Gibbs factors with their Fourier transforms, and the interactions with the variables. High (low) couplings in the interaction terms are mapped into low (high) couplings in the one-body terms. The idea is that our class of systems extends the one for which the classical procedure 'a la Kramers and Wannier holds, up to include randomness into the pattern of interaction. We introduce and study some physical examples: a random Gaussian Model, a random Potts-like model, and a random variant of discrete scalar QED. We shortly describe the consequence of duality for each example.Comment: 26 pages, 2 Postscript figure

Grassmann Integral Representation for Spanning Hyperforests

Given a hypergraph G, we introduce a Grassmann algebra over the vertex set, and show that a class of Grassmann integrals permits an expansion in terms of spanning hyperforests. Special cases provide the generating functions for rooted and unrooted spanning (hyper)forests and spanning (hyper)trees. All these results are generalizations of Kirchhoff's matrix-tree theorem. Furthermore, we show that the class of integrals describing unrooted spanning (hyper)forests is induced by a theory with an underlying OSP(1|2) supersymmetry.Comment: 50 pages, it uses some latex macros. Accepted for publication on J. Phys.

The Phase Diagram of 1-in-3 Satisfiability Problem

We study the typical case properties of the 1-in-3 satisfiability problem, the boolean satisfaction problem where a clause is satisfied by exactly one literal, in an enlarged random ensemble parametrized by average connectivity and probability of negation of a variable in a clause. Random 1-in-3 Satisfiability and Exact 3-Cover are special cases of this ensemble. We interpolate between these cases from a region where satisfiability can be typically decided for all connectivities in polynomial time to a region where deciding satisfiability is hard, in some interval of connectivities. We derive several rigorous results in the first region, and develop the one-step--replica-symmetry-breaking cavity analysis in the second one. We discuss the prediction for the transition between the almost surely satisfiable and the almost surely unsatisfiable phase, and other structural properties of the phase diagram, in light of cavity method results.Comment: 30 pages, 12 figure

Systems report for payload G-652: Project origins

Experiments conducted to investigate possible hardware configurations and methodologies for a Get Away Special payload designated G-652 are discussed. Test data collected from the operation of a free electron laser wiggler using simulated ram glow phenomenon are described. Results of an experiment to synthesize organic compounds within a primordial atmosphere using a laser induced plasma are discussed. An experiment is described which utilized neutron bombardment to assess the risk of genetic alterations in embyros in space

Risk of acute and serious liver injury associated to nimesulide and other NSAIDs: data from drug-induced liver injury case-control study in Italy

Aim: Drug-induced liver injury is one of the most serious adverse drug reactions and the most frequent reason for restriction of indications or withdrawal of drugs. Some nonsteroidal anti-inflammatory drugs (NSAIDs) were withdrawn from the market because of serious hepatotoxicity. We estimated the risk of acute and serious liver injury associated with the use of nimesulide and other NSAIDs, with a prevalence of use greater than or equal to 5%. Methods: This is a multicentre case–control study carried out in nine Italian hospitals from October 2010 to January 2014. Cases were adults, with a diagnosis of acute liver injury. Controls presented acute clinical disorders not related to chronic conditions, not involving the liver. Adjusted odds ratio (ORs) with 95% confidence interval (CI) were calculated initially with a bivariate and then multivariate analysis. Results: We included 179 cases matched to 1770 controls. Adjusted OR for acute serious liver injury associated with all NSAIDs was 1.69, 95% CI 1.21–2.37. Thirty cases were exposed to nimesulide (adjusted OR 2.10, 95% CI 1.28–3.47); the risk increased according to the length of exposure (OR > 30 days: 12.55, 95% CI 1.73–90.88) and to higher doses (OR 10.69, 95% CI 4.02–28.44). Risk of hepatotoxicity was increased also for ibuprofen, used both at recommended dosages (OR 1.92, 95% CI 1.13–3.26) and at higher doses (OR 3.73, 95% CI 1.11–12.46) and for ketoprofen ≥ 150 mg (OR 4.65, 95% CI 1.33–10.00). Conclusion: Among all NSAIDs, nimesulide is associated with the higher risk, ibuprofen and high doses of ketoprofen are also associated with a modestly increased risk of hepatotoxicity

ELISA: ELiciting ISA of Raw Binaries for Fine-grained Code and Data Separation

Static binary analysis techniques are widely used to reconstruct the behavior and discover vulnerabilities in software when source code is not available. To avoid errors due to mis-interpreting data as machine instructions (or vice-versa), disassemblers and static analysis tools must precisely infer the boundaries between code and data. However, this information is often not readily available. Worse, compilers may embed small chunks of data inside the code section. Most state of the art approaches to separate code and data are rooted on recursive traversal disassembly, with severe limitations when dealing with indirect control instructions. We propose ELISA, a technique to separate code from data and ease the static analysis of executable files. ELISA leverages supervised sequential learning techniques to locate the code section(s) boundaries of header-less binary files, and to predict the instruction boundaries inside the identified code section. As a preliminary step, if the Instruction Set Architecture (ISA) of the binary is unknown, ELISA leverages a logistic regression model to identify the correct ISA from the file content. We provide a comprehensive evaluation on a dataset of executables compiled for different ISAs, and we show that our method is capable to identify code sections with a byte-level accuracy (F1 score) ranging from 98.13% to over 99.9% depending on the ISA. Fine-grained separation of code from embedded data on x86, x86-64 and ARM executables is accomplished with an accuracy of over 99.9%

Ground-state properties of a supersymmetric fermion chain

We analyze the ground state of a strongly interacting fermion chain with a supersymmetry. We conjecture a number of exact results, such as a hidden duality between weak and strong couplings. By exploiting a scale free property of the perturbative expansions, we find exact expressions for the order parameters, yielding the critical exponents. We show that the ground state of this fermion chain and another model in the same universality class, the XYZ chain along a line of couplings, are both written in terms of the same polynomials. We demonstrate this explicitly for up to N = 24 sites, and provide consistency checks for large N. These polynomials satisfy a recursion relation related to the Painlev\'e VI differential equation, and using a scale-free property of these polynomials, we derive a simple and exact formula for their limit as N goes to infinity.Comment: v2: added more information on scaling function, fixed typo

Some geometric critical exponents for percolation and the random-cluster model

We introduce several infinite families of new critical exponents for the random-cluster model and present scaling arguments relating them to the k-arm exponents. We then present Monte Carlo simulations confirming these predictions. These new exponents provide a convenient way to determine k-arm exponents from Monte Carlo simulations. An understanding of these exponents also leads to a radically improved implementation of the Sweeny Monte Carlo algorithm. In addition, our Monte Carlo data allow us to conjecture an exact expression for the shortest-path fractal dimension d_min in two dimensions: d_min = (g+2)(g+18)/(32g) where g is the Coulomb-gas coupling, related to the cluster fugacity q via q = 2 + 2 cos(g\pi/2) with 2 \le g \le 4.Comment: LaTeX2e/Revtex4. Version 2 is completely rewritten to make the exposition more reader-friendly; it consists of a 4-page main paper (including 3 figures) and a 2-page EPAPS appendix (given as a single Postscript file). To appear in Phys Rev

Pattern of statin use in southern Italian primary care: Can prescription databases be used for monitoring long-term adherence to the treatment?

Objectives: We sought to evaluate the prescribing pattern of statins according to national and regional health policy interventions and to assess specifically the adherence to the therapy in outpatient setting in Southern Italy. Methods: A population-based study was performed on persons ≥15 years old, living in the catchment area of Caserta (Southern Italy), and registered in Arianna database between 2004 and 2010. Prevalence and incidence of new treatments with statins were calculated for each year and stratified by drug. Adherence to therapy was measured by Medication Possession Ratio. Sub-analyses by individual compound and type of cardiovascular prevention were performed. Results: From 2004 to 2010, the one-year prevalence of statin use increased from 44.9/1,000 inhabitants to 79.8/1,000, respectively, consistently with the incidence of new use from 16.2/1,000 to 19.5/1,000, except a slight decrease after criteria reimbursement revision