hagis, an R Package Resource for Pathotype Analysis of Phytophthora sojae Populations Causing Stem and Root Rot of Soybean

Phytophthora sojae is a significant pathogen of soybean worldwide. Pathotype surveys for Phytophthora sojae are conducted to monitor resistance gene efficacy and determine if new resistance genes are needed. Valuable measurements for pathotype analysis include the distribution of susceptible reactions, pathotype complexity, pathotype frequency, and diversity indices for pathotype distributions. Previously the Habgood-Gilmour Spreadsheet (HaGiS), written in Microsoft Excel, was used for data analysis. However, the growing popularity of the R programming language in plant pathology and desire for reproducible research made HaGiS a prime candidate for conversion into an R package. Here we report on the development and use of an R package, hagis, that can be used to produce all outputs from the HaGiS Excel sheet for P. sojae or other gene-for-gene pathosystem studies

Exact solution of a 2d random Ising model

The model considered is a d=2 layered random Ising system on a square lattice with nearest neighbours interaction. It is assumed that all the vertical couplings are equal and take the positive value J while the horizontal couplings are quenched random variables which are equal in the same row but can take the two possible values J and J-K in different rows. The exact solution is obtained in the limit case of infinite K for any distribution of the horizontal couplings. The model which corresponds to this limit can be seen as an ordinary Ising system where the spins of some rows, chosen at random, are frozen in an antiferromagnetic order. No phase transition is found if the horizontal couplings are independent random variables while for correlated disorder one finds a low temperature phase with some glassy properties.Comment: 10 pages, Plain TeX, 3 ps figures, submitted to Europhys. Let

A Relevance Model for Threat-Centric Ranking of Cybersecurity Vulnerabilities

The relentless and often haphazard process of tracking and remediating vulnerabilities is a top concern for cybersecurity professionals. The key challenge they face is trying to identify a remediation scheme specific to in-house, organizational objectives. Without a strategy, the result is a patchwork of fixes applied to a tide of vulnerabilities, any one of which could be the single point of failure in an otherwise formidable defense. This means one of the biggest challenges in vulnerability management relates to prioritization. Given that so few vulnerabilities are a focus of real-world attacks, a practical remediation strategy is to identify vulnerabilities likely to be exploited and focus efforts towards remediating those vulnerabilities first. The goal of this research is to demonstrate that aggregating and synthesizing readily accessible, public data sources to provide personalized, automated recommendations that an organization can use to prioritize its vulnerability management strategy will offer significant improvements over what is currently realized using the Common Vulnerability Scoring System (CVSS). We provide a framework for vulnerability management specifically focused on mitigating threats using adversary criteria derived from MITRE ATT&CK. We identify the data mining steps needed to acquire, standardize, and integrate publicly available cyber intelligence data sets into a robust knowledge graph from which stakeholders can infer business logic related to known threats. We tested our approach by identifying vulnerabilities in academic and common software associated with six universities and four government facilities. Ranking policy performance was measured using the Normalized Discounted Cumulative Gain (nDCG). Our results show an average 71.5% to 91.3% improvement towards the identification of vulnerabilities likely to be targeted and exploited by cyber threat actors. The ROI of patching using our policies resulted in a savings in the range of 23.3% to 25.5% in annualized unit costs. Our results demonstrate the efficiency of creating knowledge graphs to link large data sets to facilitate semantic queries and create data-driven, flexible ranking policies. Additionally, our framework uses only open standards, making implementation and improvement feasible for cyber practitioners and academia

The Spin-Spin Correlation Function in the Two-Dimensional Ising Model in a Magnetic Field at T=TcT=T_c

The form factor bootstrap approach is used to compute the exact contributions in the large distance expansion of the correlation function $<\sigma(x) \sigma(0)>$ of the two-dimensional Ising model in a magnetic field at $T=T_c$. The matrix elements of the magnetization operator $\sigma(x)$ present a rich analytic structure induced by the (multi) scattering processes of the eight massive particles of the model. The spectral representation series has a fast rate of convergence and perfectly agrees with the numerical determination of the correlation function.Comment: 53 pages, latex, 15 figure

Spin Chains as Perfect Quantum State Mirrors

Quantum information transfer is an important part of quantum information processing. Several proposals for quantum information transfer along linear arrays of nearest-neighbor coupled qubits or spins were made recently. Perfect transfer was shown to exist in two models with specifically designed strongly inhomogeneous couplings. We show that perfect transfer occurs in an entire class of chains, including systems whose nearest-neighbor couplings vary only weakly along the chain. The key to these observations is the Jordan-Wigner mapping of spins to noninteracting lattice fermions which display perfectly periodic dynamics if the single-particle energy spectrum is appropriate. After a half-period of that dynamics any state is transformed into its mirror image with respect to the center of the chain. The absence of fermion interactions preserves these features at arbitrary temperature and allows for the transfer of nontrivially entangled states of several spins or qubits.Comment: Abstract extended, introduction shortened, some clarifications in the text, one new reference. Accepted by Phys. Rev. A (Rapid Communications

Form factor expansion of the row and diagonal correlation functions of the two dimensional Ising model

We derive and prove exponential and form factor expansions of the row correlation function and the diagonal correlation function of the two dimensional Ising model

Non-integrable Quantum Field Theories as Perturbations of Certain Integrable Models

We approach the study of non--integrable models of two--dimensional quantum field theory as perturbations of the integrable ones. By exploiting the knowledge of the exact $S$-matrix and Form Factors of the integrable field theories we obtain the first order corrections to the mass ratios, the vacuum energy density and the $S$-matrix of the non-integrable theories. As interesting applications of the formalism, we study the scaling region of the Ising model in an external magnetic field at $T \sim T_c$ and the scaling region around the minimal model $M_{2,7}$. For these models, a remarkable agreement is observed between the theoretical predictions and the data extracted by a numerical diagonalization of their Hamiltonian.Comment: 60 pages, latex, 9 figure

Randomly incomplete spectra and intermediate statistics

By randomly removing a fraction of levels from a given spectrum a model is constructed that describes a crossover from this spectrum to a Poisson spectrum. The formalism is applied to the transitions towards Poisson from random matrix theory (RMT) spectra and picket fence spectra. It is shown that the Fredholm determinant formalism of RMT extends naturally to describe incomplete RMT spectra.Comment: 9 pages, 2 figures. To appear in Physical Review

Lifespan theorem for constrained surface diffusion flows

We consider closed immersed hypersurfaces in $\R^{3}$ and $\R^4$ evolving by a class of constrained surface diffusion flows. Our result, similar to earlier results for the Willmore flow, gives both a positive lower bound on the time for which a smooth solution exists, and a small upper bound on a power of the total curvature during this time. By phrasing the theorem in terms of the concentration of curvature in the initial surface, our result holds for very general initial data and has applications to further development in asymptotic analysis for these flows.Comment: 29 pages. arXiv admin note: substantial text overlap with arXiv:1201.657