Efficient Monitoring of Parametric Context Free Patterns

Recent developments in runtime verification and monitoring show that parametric regular and temporal logic specifications can be efficiently monitored against large programs. However, these logics reduce to ordinary finite automata, limiting their expressivity. For example, neither can specify structured properties that refer to the call stack of the program. While context-free grammars (CFGs) are expressive and well-understood, existing techniques of monitoring CFGs generate massive runtime overhead in real-life applications. This paper shows for the first time that monitoring parametric CFGs is practical (on the order of 10% or lower for average cases, several times faster than the state-of-the-art). We present a monitor synthesis algorithm for CFGs based on an LR(1) parsing algorithm, modified with stack cloning to account for good prefix matching. In addition, a logic-independent mechanism is introduced to support partial matching, allowing patterns to be checked against fragments of execution traces

Lightweight Call-Graph Construction for Multilingual Software Analysis

Analysis of multilingual codebases is a topic of increasing importance. In prior work, we have proposed the MLSA (MultiLingual Software Analysis) architecture, an approach to the lightweight analysis of multilingual codebases, and have shown how it can be used to address the challenge of constructing a single call graph from multilingual software with mutual calls. This paper addresses the challenge of constructing monolingual call graphs in a lightweight manner (consistent with the objective of MLSA) which nonetheless yields sufficient information for resolving language interoperability calls. A novel approach is proposed which leverages information from a compiler-generated AST to provide the quality of call graph necessary, while the program itself is written using an Island Grammar that parses the AST providing the lightweight aspect necessary. Performance results are presented for a C/C++ implementation of the approach, PAIGE (Parsing AST using Island Grammar Call Graph Emitter) showing that despite its lightweight nature, it outperforms Doxgen, is robust to changes in the (Clang) AST, and is not restricted to C/C++.Comment: 10 page

Douglas Dynamics, Inc. A Financial Analysis and Valuation Report

Douglas Dynamics, Inc. was founded in 1977 and is one of the many construction machinery companies in the industry. Their headquarters is located in Milwaukee, WI, but they sell products in the United States, Canada, Northern Europe, and Asia. The company consist of two segments, a Work Truck Attachment, and a Work Truck Solutions. Having these two segments allow the company to reach into different markets, but the main market is snow and ice management. They have been able to stay ahead of the competition by acquiring other construction machinery businesses and innovating their current products. In the beginning of 2019, the company appointed a new President and CEO, Robert McCormick. He has had various roles in the company for the last 15 years. This report comprises historical financial analysis from 2014 to 2019 and current valuation of the business. There are also financial comparisons to another company, which is a member of the same industry and is located in the same region. Since 2014, the company has had steady quality of earnings ratio and activity ratios. In all of these years’ annual reports, there were no material deficiencies reported in the test of internal controls, and external auditors gave unqualified opinions on the financials. Based on the analysis, I believe this stock is undervalued. I recommend that you buy this stock as I believe it is worth more than the current price on 12/31/2020. Purchasing this stock at lower cost than valued, there is opportunity for long term profit as it is expected to increase in price

Synthèse de nouveaux ligands thiacalixaréniques et étude de leurs propriétés de complexation

8 pagesNational audienceLes perspectives ouvertes par la chimie supramoléculaire sont immenses notamment dans le domaine biomimétique mais aussi à l'interface avec la physique et la science des matériaux. Dans ce contexte nous nous sommes intéressés à une famille de macrocycles synthétiques appelés thiacalixarènes. De nouveaux ligands ont été préparés et leurs propriétés de complexation ont été étudiées vis-à-vis de métaux lourds et de métaux de transition. Ces récepteurs ont été conçus de telle façon qu'ils puissent être fixés sur des supports, leur permettant alors d'être utilisés en phase solide – liquide

Synthesis and conformational studies of chiral macrocyclic [1.1.1]metacyclophanes containing benzofuran rings

Macrocyclic [1.1.1]metacyclophanes (MCPs) containing benzene and benzofuran rings linked by methylene bridges and which can be viewed as calixarene analogues, have been synthesized by demethylation of [3.3.1]MCP-diones with trimethylsilyl iodide (TMSI) in MeCN. The [3.3.1]MCP-diones are synthesized by using (p-tolylsulfonyl)methyl isocyanide (TosMIC) as the cyclization reagent in N,N-dimethylformamide (DMF) with an excess of sodium hydride. ¹H NMR spectroscopy revealed that the remaining hydroxyl group on the phenyl ring is involved in intramolecular hydrogen bonding with the oxygen of one of the benzofuran rings. O-Methylation at the lower rim of monohydroxy[1.1.1]MCP in the presence of K₂CO₃ in acetone afforded a novel and inherently chiral calixarene analogue, namely the macrocyclic [1.1.1]MCP, possessing C₁ symmetry. The inherent chirality of the two conformers was characterized by ¹H NMR spectroscopy by addition of an excess of Pirkle's chiral shift reagent, which caused a splitting of the corresponding methylene protons to AB patterns. Single crystal X-ray analysis revealed the adoptation of a hemisphere-shaped cone isomer. DFT calculations were carried out to investigate the energy-minimized structures and the hydrogen bonds of the synthesized MCPs

NeuroEVs: Characterizing Extracellular Vesicles Generated in the Neural Domain.

Intercellular communication has recently been shown to occur via transfer of cargo loaded within extracellular vesicles (EVs). Present within all biofluids of the body, EVs can contain various signaling factors, including coding and noncoding RNAs (e.g., mRNA, miRNA, lncRNA, snRNA, tRNA, yRNA), DNA, proteins, and enzymes. Multiple types of cells appear to be capable of releasing EVs, including cancer, stem, epithelial, immune, glial, and neuronal cells. However, the functional impact of these circulating signals among neural networks within the brain has been difficult to establish given the complexity of cellular populations involved in release and uptake, as well as inherent limitations of examining a biofluid. In this brief commentary, we provide an analysis of the conceptual and technical considerations that limit our current understanding of signaling mediated by circulating EVs relative to their impact on neural function