Metamodel-based model conformance and multiview consistency checking

Model-driven development, using languages such as UML and BON, often makes use of multiple diagrams (e.g., class and sequence diagrams) when modeling systems. These diagrams, presenting different views of a system of interest, may be inconsistent. A metamodel provides a unifying framework in which to ensure and check consistency, while at the same time providing the means to distinguish between valid and invalid models, that is, conformance. Two formal specifications of the metamodel for an object-oriented modeling language are presented, and it is shown how to use these specifications for model conformance and multiview consistency checking. Comparisons are made in terms of completeness and the level of automation each provide for checking multiview consistency and model conformance. The lessons learned from applying formal techniques to the problems of metamodeling, model conformance, and multiview consistency checking are summarized

Multiple-Purpose Subsonic Naval Aircraft (MPSNA): Multiple Application Propfan Study (MAPS)

Study requirements, assumptions and guidelines were identified regarding carrier suitability, aircraft missions, technology availability, and propulsion considerations. Conceptual designs were executed for two missions, a full multimission aircraft and a minimum mission aircraft using three different propulsion systems, the UnDucted Fan (UDF), the Propfan and an advanced Turbofan. Detailed aircraft optimization was completed on those configurations yielding gross weight performance and carrier spot factors. Propfan STOVL conceptual designs were exercised also to show the effects of STOVL on gross weight, spot factor and cost. An advanced technology research plan was generated to identify additional investigation opportunities from an airframe contractors standpoint. Life cycle cost analysis was accomplished yielding a comparison of the UDF and propfan configurations against each other as well as against a turbofan with equivalent state of the art turbo-machinery

Compositional Performance Modelling with the TIPPtool

Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art techniques, and wrapped in a user-friendly graphical front end. Apart from highlighting the general benefits of the tool, we also discuss some lessons learned during development and application of the TIPPtool. A non-trivial model of a real life communication system serves as a case study to illustrate benefits and limitations

Flora and Fauna in East Asian Art

Flora and Fauna in East Asian Art is the fourth annual exhibition curated by students enrolled in the Art History Methods course. This exhibition highlights the academic achievements of six student curators: Samantha Frisoli ’18, Daniella Snyder ’18, Gabriella Bucci ’19, Melissa Casale ’19, Keira Koch ’19, and Paige Deschapelles ’20. The selection of artworks in this exhibition considers how East Asian artists portrayed similar subjects of flora and fauna in different media including painting, prints, embroidery, jade, and porcelain. This exhibition intends to reveal the hidden meanings behind various representations of flora and fauna in East Asian art by examining the iconography, cultural context, aesthetic and function of each object.https://cupola.gettysburg.edu/artcatalogs/1025/thumbnail.jp

Enhanced Operational Semantics in Systems Biology

We are faced with a great challenge: the cross-fertilization between the fields of formal methods for concurrency, in the computer science domain, and systems biology in the biological realm

Immune factors preceding diagnosis of glioma: a Prostate Lung Colorectal Ovarian Cancer Screening Trial nested case-control study.

BackgroundEpidemiological studies of adult glioma have identified genetic and environmental risk factors, but much remains unclear. The aim of the current study was to evaluate anthropometric, disease-related, and prediagnostic immune-related factors for relationship with glioma risk.MethodsWe conducted a nested case-control study among the intervention arm of the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. One hundred and twenty-four glioma cases were identified and each matched to four controls. Baseline characteristics were collected at enrollment and were evaluated for association with glioma status. Serum specimens were collected at yearly intervals and were analyzed for immune-related factors including TGF-β1, TNF-α, total IgE, and allergen-specific IgE. Immune factors were evaluated at baseline in a multivariate conditional logistic regression model, along with one additional model that incorporated the latest available measurement.ResultsA family history of glioma among first-degree relatives was associated with increased glioma risk (OR = 4.41, P = .002). In multivariate modeling of immune factors at baseline, increased respiratory allergen-specific IgE was inversely associated with glioma risk (OR for allergen-specific IgE > 0.35 PAU/L: 0.59, P = .03). A logistic regression model that incorporated the latest available measurements found a similar association for allergen-specific IgE (P = .005) and showed that elevated TGF-β1 was associated with increased glioma risk (P-value for trend <.0001).ConclusionThe results from this prospective prediagnostic study suggest that several immune-related factors are associated with glioma risk. The association observed for TGF-β1 when sampling closer to the time of diagnosis may reflect the nascent brain tumor's feedback on immune function

Faster variational quantum algorithms with quantum kernel-based surrogate models

We present a new optimization method for small-to-intermediate scale variational algorithms on noisy near-term quantum processors which uses a Gaussian process surrogate model equipped with a classically-evaluated quantum kernel. Variational algorithms are typically optimized using gradient-based approaches however these are difficult to implement on current noisy devices, requiring large numbers of objective function evaluations. Our scheme shifts this computational burden onto the classical optimizer component of these hybrid algorithms, greatly reducing the number of queries to the quantum processor. We focus on the variational quantum eigensolver (VQE) algorithm and demonstrate numerically that such surrogate models are particularly well suited to the algorithm's objective function. Next, we apply these models to both noiseless and noisy VQE simulations and show that they exhibit better performance than widely-used classical kernels in terms of final accuracy and convergence speed. Compared to the typically-used stochastic gradient-descent approach for VQAs, our quantum kernel-based approach is found to consistently achieve significantly higher accuracy while requiring less than an order of magnitude fewer quantum circuit evaluations. We analyse the performance of the quantum kernel-based models in terms of the kernels' induced feature spaces and explicitly construct their feature maps. Finally, we describe a scheme for approximating the best-performing quantum kernel using a classically-efficient tensor network representation of its input state and so provide a pathway for scaling these methods to larger systems

On strongly chordal graphs that are not leaf powers

A common task in phylogenetics is to find an evolutionary tree representing proximity relationships between species. This motivates the notion of leaf powers: a graph G = (V, E) is a leaf power if there exist a tree T on leafset V and a threshold k such that uv is an edge if and only if the distance between u and v in T is at most k. Characterizing leaf powers is a challenging open problem, along with determining the complexity of their recognition. This is in part due to the fact that few graphs are known to not be leaf powers, as such graphs are difficult to construct. Recently, Nevries and Rosenke asked if leaf powers could be characterized by strong chordality and a finite set of forbidden subgraphs. In this paper, we provide a negative answer to this question, by exhibiting an infinite family \G of (minimal) strongly chordal graphs that are not leaf powers. During the process, we establish a connection between leaf powers, alternating cycles and quartet compatibility. We also show that deciding if a chordal graph is \G-free is NP-complete, which may provide insight on the complexity of the leaf power recognition problem

C\u3csub\u3e60\u3c/sub\u3e and Sc\u3csub\u3e3\u3c/sub\u3eN@C\u3csub\u3e80\u3c/sub\u3e(TMB-PPO) Derivatives as Constituents of Singlet Oxygen Generating, Thiol-ene Polymer Nanocomposites

Numerous functionalization methods have been employed to increase the solubility, and therefore, the processability of fullerenes in composite structures, and of these radical addition reactions continue to be an important methodology. C60 and Sc3N@C80 derivatives were prepared via radical addition of the photodecomposition products from the commercial photoinitiator TMB-PPO, yielding C60(TMB-PPO)5 and Sc3N@C80(TMB-PPO)3 as preferred soluble derivatives obtained in high yields. Characterization of the mixture of isomers using standard techniques suggests an overall 1PPO:6TMB ratio of addends, reflecting the increased reactivity of the carbon radical. Although, a higher percentage of PPO is observed in the Sc3N@C80(TMB-PPO)3 population, perhaps due to reverse electronic requirements of the substrate. Visually dispersed thiol-ene nanocomposites with low extractables were prepared using two monomer compositions (PETMP:TTT and TMPMP:TMPDE) with increasing fullerene derivative loading to probe network structure-property relationships. Thermal stability of the derivatives and the resulting networks decreased with increased functionality and at high fullerene loadings, respectively. TMPMP:TMPDE composite networks show well-dispersed derivatives via TEM imaging, and increasing Tg’s with fullerene loading, as expected for the incorporation of a more rigid network component. PETMP:TTT composites show phase separation in TEM, which is supported by the observed Tg’s. Singlet oxygen generation of the derivatives decreases with increased functionality; however, this is compensated for by the tremendous increase in solubility in organic solvents and miscibility with monomers. Most importantly, singlet oxygen generation from the composites increased with fullerene derivative loading, with good photostability of the networks

Program transformations using temporal logic side conditions

This paper describes an approach to program optimisation based on transformations, where temporal logic is used to specify side conditions, and strategies are created which expand the repertoire of transformations and provide a suitable level of abstraction. We demonstrate the power of this approach by developing a set of optimisations using our transformation language and showing how the transformations can be converted into a form which makes it easier to apply them, while maintaining trust in the resulting optimising steps. The approach is illustrated through a transformational case study where we apply several optimisations to a small program