Novel dyes based on a 3-formyl-2(1H)-quinolone skeleton were synthesised and characterised using 1 H nuclear magnetic resonance spectroscopy and mass spectrometry. The spectroscopic properties of these dyes, such as their absorption spectra, emission spectra, and quantum fluorescence yields, were also examined. The behaviour of the obtained compounds at a pH of 7.4 in the absence and in the presence of thiol amino acids, such as L-cysteine, L-glutathione, and N-acetyl-L-cysteine, were studied. The spectroscopic responses of the tested dyes towards other amino acids were also investigated. A reference compound was synthesised to understand the reaction mechanism between the thiols and the obtained dyes. The experimental results show that the synthesised dyes have the potential to act as sensors for thiols.
Coloration TechnologySociety of Dyers and Colourists 157
Presently, Electrical Capacitance Tomography (ECT) is positioned as a relatively mature and inexpensive tool for the diagnosis of non-conductive industrial processes. For most industrial applications, a hand-made approach for an ECT sensor and its 3D extended structure fabrication is used. Moreover, a hand-made procedure is often inaccurate, complicated, and time-consuming. Another drawback is that a hand-made ECT sensor’s geometrical parameters, mounting base profile thickness, and electrode array shape usually depends on the structure of industrial test objects, tanks, and containers available on the market. Most of the traditionally fabricated capacitance tomography sensors offer external measurements only with electrodes localized outside of the test object. Although internal measurement is possible, it is often difficult to implement. This leads to limited in-depth scanning abilities and poor sensitivity distribution of traditionally fabricated ECT sensors. In this work we propose, demonstrate, and validate experimentally a new 3D ECT sensor fabrication process. The proposed solution uses a computational workflow that incorporates both 3D computer modeling and 3D-printing techniques. Such a 3D-printed structure can be of any shape, and the electrode layout can be easily fitted to a broad range of industrial applications. A developed solution offers an internal measurement due to negligible thickness of sensor mount base profile. This paper analyses and compares measurement capabilities of a traditionally fabricated 3D ECT sensor with novel 3D-printed design. The authors compared two types of the 3D ECT sensors using experimental capacitance measurements for a set of low-contrast and high-contrast permittivity distribution phantoms. The comparison demonstrates advantages and benefits of using the new 3D-printed spatial capacitance sensor regarding the significant fabrication time reduction as well as the improvement of overall measurement accuracy and stability.
Several 6‐pyridinium benzo[a]phenazine‐5‐oxide derivatives have been synthesised and characterised by proton nuclear magnetic resonance spectroscopy and mass spectrometry. The spectroscopic and electrochemical properties of these dyes were examined. The dyes were used as reducible sensitisers for selected electron donors (phenylthioacetic acid, phenoxyacetic acid, N‐phenylglycine, and ethyl 4‐N,N‐dimethylaminobenzoate) and as oxidisable sensitisers for electron acceptors (onium and N‐alkoxypyridinium salts). These photoredox pairs were found to be effective visible‐wavelength photoinitiators for the free radical polymerisation of trimethylolpropane triacrylate under visible light. The cationic photopolymerisation of cyclohexene oxide by the studied dyes and the onium salt photoredox pairs was ineffective. The obtained results are discussed on the basis of both free energy change for electron transfer to or from the benzo[a]phenazine dyes and the photochemical properties of the dyes, particularly their photobleaching. The proposed mechanism of dye fading is supported by density functional theory calculations and spectroscopic characterisation of the radical cation of the dye.
This paper presents an overview of what Big Data can bring to the modern industry. Through following the history of contemporary Big Data frameworks the authors observe that the tools available have reached sufficient maturity so as to be usable in an industrial setting. The authors propose the concept of a system for collecting, organising, processing and analysing experimental data obtained from measurements with process tomography. Process tomography is used for noninvasive flow monitoring and data acquisition. The measurement data is collected, stored and processed to identify process regimes and process threats. Further general examples of solutions that aim to take advantage of the existence of such tools are presented as proof of viability of such approach. As the first step in the process of creating the proposed system, a scalable, distributed, containerisation-based cluster has been constructed, with consumer-grade hardware.
Learning outcomes are measurable statements that articulate educational aims in terms of what knowledge, skills, and other competences students possess after successfully completing a given learning experience. This paper presents an analysis of the disparity between the claimed and formulated learning outcomes categorized in knowledge, skills, and social responsibility competency classes as it is postulated in the European Qualification Framework. We employed machine learning classification algorithms to detect and reveal main errors in their formulation that result in incorrect classification using generally available syllabus data from 22 universities. The proposed method was employed in two stages: preprocessing (creating a Python dataframe structure) and classification (by performing tokenization with the term frequency–inverse document frequency method). The obtained results demonstrated high effectiveness in correct classification for a number of machine learning algorithms. The obtained sensitivity and specificity reached 0.8 for most cases with acceptable positive predictive values for social responsibility competency classes and relatively high negative predictive values greater than 0.8 for all classes. Hence, the presented methodology and results may be a prelude to conducting further studies associated with identifying learning outcomes.
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