Concrete Semantics with Coq and CoqHammer

The "Concrete Semantics" book gives an introduction to imperative programming languages accompanied by an Isabelle/HOL formalization. In this paper we discuss a re-formalization of the book using the Coq proof assistant. In order to achieve a similar brevity of the formal text we extensively use CoqHammer, as well as Coq Ltac-level automation. We compare the formalization efficiency, compactness, and the readability of the proof scripts originating from a Coq re-formalization of two chapters from the book

Studies of ignition behaviour of biomass particles in a down-fire reactor for improving co-firing performance

To realize large percentage biomass co-firing with coal in existing coal-fired boilers, the combustion behaviour of biomass is expected to be similar or comparable to that of coal. When co-firing with coal, biomass is not necessarily to be ground as fine as the dedicated coal particles due to its higher reactivity. With aim of achieving promising performance of co-firing with dedicated coal particles, the determination of suitable particle size of biomass becomes important. The paper investigates experimentally the ignition behaviour of three biomass materials in a down-fire reactor associated with thermogravimetric analyser (TGA). TGA results showed that the devolatilization process is accelerated by the presence of oxygen, but failed to identify the impacts of particle size on the ignition behaviour of biomass. However, the ignition testing results based in the down-fire reactor clearly showed that ignition delay time of a large biomass particle is longer than that of smaller one. In addition, being injected into the furnace, the softwood particles take a longer residence time to be ignited than the straw particles at same sizes, which agrees well with their reactivity analysis in TGA. Moreover, the ignition test results suggested that the ignition mechanism of biomass could be alternated from homogeneous to the heterogeneous ignition when the furnace temperature is increasing; at high enough furnace temperatures, the ignition predictably occurs at the particle surface without requiring the start of devolatilization. The results quantitatively demonstrate the effects of particle size on the ignition delay time of biomass , which, together with the transport phenomena and surrounding atmosphere, can contribute to control the biomass combustion profile and co-firing performance

Studies of ignition behaviour of biomass particles in a down-fire reactor for improving co-firing performance

To realize large percentage biomass co-firing with coal in existing coal-fired boilers, the combustion behaviour of biomass is expected to be similar or comparable to that of coal. When co-firing with coal, biomass is not necessarily to be ground as fine as the dedicated coal particles due to its higher reactivity. With aim of achieving promising performance of co-firing with dedicated coal particles, the determination of suitable particle size of biomass becomes important. The paper investigates experimentally the ignition behaviour of three biomass materials in a down-fire reactor associated with thermogravimetric analyser (TGA). TGA results showed that the devolatilization process is accelerated by the presence of oxygen, but failed to identify the impacts of particle size on the ignition behaviour of biomass. However, the ignition testing results based in the down-fire reactor clearly showed that ignition delay time of a large biomass particle is longer than that of smaller one. In addition, being injected into the furnace, the softwood particles take a longer residence time to be ignited than the straw particles at same sizes, which agrees well with their reactivity analysis in TGA. Moreover, the ignition test results suggested that the ignition mechanism of biomass could be alternated from homogeneous to the heterogeneous ignition when the furnace temperature is increasing; at high enough furnace temperatures, the ignition predictably occurs at the particle surface without requiring the start of devolatilization. The results quantitatively demonstrate the effects of particle size on the ignition delay time of biomass , which, together with the transport phenomena and surrounding atmosphere, can contribute to control the biomass combustion profile and co-firing performance

The Tactician (extended version): A Seamless, Interactive Tactic Learner and Prover for Coq

We present Tactician, a tactic learner and prover for the Coq Proof Assistant. Tactician helps users make tactical proof decisions while they retain control over the general proof strategy. To this end, Tactician learns from previously written tactic scripts and gives users either suggestions about the next tactic to be executed or altogether takes over the burden of proof synthesis. Tactician's goal is to provide users with a seamless, interactive, and intuitive experience together with robust and adaptive proof automation. In this paper, we give an overview of Tactician from the user's point of view, regarding both day-to-day usage and issues of package dependency management while learning in the large. Finally, we give a peek into Tactician's implementation as a Coq plugin and machine learning platform.Comment: 19 pages, 2 figures. This is an extended version of a paper published in CICM-2020. For the project website, see https://coq-tactician.github.i

Physicochemical and Antibacterial Characterisation of a Novel Fluorapatite Coating

Peri-implantitis remains the major impediment to the long-term use of dental implants. With increasing concern over growing antibiotic resistance there is considerable interest in the preparation of antimicrobial dental implant coatings that also induce osseointegration. One such potential coating material is fluorapatite (FA). The aim of this study was to relate the antibacterial effectiveness of FA coatings against pathogens implicated in peri-implantitis to the physicochemical properties of the coating. Ordered and disordered FA coatings were produced on the under and upper surface of stainless steel (SS) discs respectively, using a hydrothermal method. Surface charge, surface roughness, wettability and fluoride release were measured for each coating. Surface chemistry was assessed by X-ray photoelectron spectroscopy and FA crystallinity by X-ray diffraction. Antibacterial activity against periodontopathogens was assessed in vitro using viable counts, confocal and scanning electron (SEM) microscopies. SEM showed that the hydrothermal method produced FA coatings predominately aligned perpendicular to the SS substrate or disordered FA coatings consisting of randomly aligned rod-like crystals. Both FA coatings significantly reduced the growth of all the examined bacterial strains in comparison to the control. The FA coatings, and especially the disordered ones, presented significantly lower charge, higher roughness and area when compared to the control, enhancing bacteria–material interactions and therefore bacterial deactivation by fluoride ions. The ordered FA layer reduced not only bacterial viability but adhesion too. Ordered FA crystals produced as a potential novel implant coating showed significant antibacterial activity against bacteria implicated in peri-implantitis which could be explained by a detailed understanding of their physicochemical properties

BayFlux: A Bayesian Method to Quantify Metabolic Fluxes and their Uncertainty at the Genome Scale.

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13C Metabolic Flux Analysis (13C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in “non-gaussian” situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P-13C MOMA and P-13C ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods by quantifying prediction uncertainty

Trimethylsilyl hedgehogs - A novel class of super-efficient hydrocarbon surfactants

Presented here are the results for a novel class of hydrocarbon surfactants, termed trimethylsilyl hedgehogs (TMS-hedgehogs), due to the presence of silicon in the tails.</p