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Search results for: MACHINE LEARNING, 3D-PRINTED FIBER REINFORCED CONCRETE, MODEL INTERPRETABILITY, COMPRESSIVE STRENGTH
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Monitoring of concrete curing in extradosed bridge supported by numerical simulation
PublicationThe paper describes a mathematical model of concrete curing taking into account kinetics of setting reactions. The numerical model is implemented in the author’s program that was used to monitor thermal effects recorded in the concrete bottom plate of the extradosed bridge. Numerical approach was verified by experimental measurements and used for assessment of the current compressive strength due to degree of hydration of fresh...
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Corrosion behavior of concrete produced with diatomite and zeolite exposed to chlorides
PublicationChloride induced reinforcement corrosion is widely accepted to be the most frequent mechanism causing premature degradation of reinforced concrete structures. The electrochemical impedance of reinforcing steel in diatomite- and zeolite-containing concrete exposed to sodium chloride was assessed. Chemical, physical and mineralogical properties of three concrete samples (20% diatomite, 20% zeolite, and a reference containing neither)...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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3-D finite-difference time-domain modelling of ground penetrating radar for identification of rebars in complex reinforced concrete structures
PublicationThis paper presents numerical and experimental investigations to identify reinforcing bars using the ground penetrating radar (GPR) method. A novel element of the paper is the inspection of different arrangements of reinforcement bars. Two particular problems, i.e. detection of few adjacent transverse bars and detection of a longitudinal bar located over or under transverse reinforcement, have been raised. An attention was also...
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Fatigue Performance of Double-Layered Asphalt Concrete Beams Reinforced with New Type of Geocomposites
PublicationThe reinforcement of asphalt layers with geosynthetics has been used for several decades, but proper evaluation of the influence of these materials on pavement fatigue life is still a challenging task. The presented study investigates a novel approach to the reinforcement of asphalt layers using a new type of geogrid composite, in which square or hexagonal polypropylene stiff monolithic paving grid with integral junctions is bonded...
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MagMax: Leveraging Model Merging for Seamless Continual Learning
PublicationThis paper introduces a continual learning approach named MagMax, which utilizes model merging to enable large pre-trained models to continuously learn from new data without forgetting previously acquired knowledge. Distinct from traditional continual learning methods that aim to reduce forgetting during task training, MagMax combines sequential fine-tuning with a maximum magnitude weight selection for effective knowledge integration...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Effect of steel fibres on concrete behavior in 2D and 3D simulations using lattice model.
PublicationW artykule przedstawiono wyniki numerycznej symulacji betonu zbrojonego włóknami stalowymi. Beton został opisany w skali mezo jako materiał 3-fazowy przy zastosowaniu modelu sieciowego. Obliczenia wykonano dla rozciągania jednoosiowego. Porównano ze sobą wyniki dwu- i trójwymiarowe.
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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Electrochemical investigations of conductive coatings applied as anodes in cathodic protection of reinforced concrete
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Investigations on strength and fracture in RC beams scaled along height or length
PublicationThe objective of the present paper is to identify experimentally and theoretically differing failure mechanisms in reinforced concrete beams subjected to four-point bending for a separate variation of the depth and length at the constant thickness. Experiments were performed on reinforced concrete beams under four-point bending. Different failure mechanisms included steel yielding, diagonal tension or shear- compression depending...
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Seismic probabilistic assessment of steel and reinforced concrete structures including earthquake-induced pounding
PublicationRecent earthquakes demonstrate that prioritizing the retrofitting of buildings should be of the utmost importance for enhancing the seismic resilience and structural integrity of urban structures. To have a realistic results of the pounding effects in modeling process of retrofitting buildings, the present research provides seismic Probability Factors (PFs), which can be used for estimating collision effects without engaging in...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublicationThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Helium-assisted, solvent-free electro-activation of 3D printed conductive carbon-polylactide electrodes
PublicationFused filament fabrication is one of the most rapidly developing 3D printing techniques, with numerous applications, including in the field of applied electrochemistry. Here, the utilisation of conductive carbon black polylactic acid (CB-PLA) for 3D printouts is the most promising. To use CB-PLA as an electrode material, an activation process must be performed, removing the polymer matrix and uncovering the electrically conductive...
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Computers and Concrete
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Laboratory fatigue assessment of large geocomposite-reinforced double-layered asphalt concrete beams
PublicationGeosynthetic reinforcement of asphalt layers has been used for several decades. Evaluation of the influence of these materials on pavement fatigue life is still ongoing, especially for new types of geocomposites. This paper presents the evaluation of fatigue performance of large asphalt concrete beams reinforced with a new type of composite in which square or hexagonal polypropylene stiff monolithic paving grid with integral junctions...
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Laboratory fatigue assessment of large geocomposite-reinforced double-layered asphalt concrete beams
PublicationGeosynthetic reinforcement of asphalt layers has been used for several decades. Evaluation of the influence of these materials on pavement fatigue life is still ongoing, especially for new types of geocomposites. This paper presents the evaluation of fatigue performance of large asphalt concrete beams reinforced with a new type of composite in which square or hexagonal polypropylene stiff monolithic paving grid with integral junctions...
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Influence of low-temperature physical hardening on stiffness and tensile strength of asphalt concrete and stone mastic asphalt
PublicationThis paper presents laboratory testing of stiffness modulus and indirect tensile strength of three asphalt concrete (AC) and three stone mastic asphalt (SMA) mixes after isothermal storage at temperature of -20oC, at different time intervals up to 16 days. The tests under repeated dynamic loading showed physical hardening of all tested mixes which was manifested by an evident increase of their stiffness moduli after isothermal...
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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublicationAchieving compact size has emerged as a key consideration in modern microwave design. While structural miniaturization can be accomplished through judicious circuit architecture selection, precise parameter tuning is equally vital to minimize physical dimensions while meeting stringent performance requirements for electrical characteristics. Due to the intricate nature of compact structures, global optimization is recommended,...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Processing of Polyester-Urethane Filament and Characterization of FFF 3D Printed Elastic Porous Structures with Potential in Cancellous Bone Tissue Engineering
PublicationThis paper addresses the potential of self-made polyester-urethane filament as a candidate for Fused Filament Fabrication (FFF)-based 3D printing (3DP) in medical applications. Since the industry does not provide many ready-made solutions of medical-grade polyurethane filaments, we undertook research aimed at presenting the process of thermoplastic polyurethane (TPU) filament formation, detailed characteristics, and 3DP of specially...
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Minimal transverse reinforcement of reinforced concrete members
PublicationW pierwszej części pracy omówiono zagadnienia dotyczące minimalnego zbrojenia na ścinanie elementów żelbetowych w kontekście norm europejskich oraz pozaeuropejskich. W drugiej części pracy dokonano analizy wyników badań eksperymentalnych dotyczących nośności elementów bez zbrojenia poprzecznego, które stanowią podstawę do weryfikacji zaleceń normowych w zakresie minimalnego zbrojenia na ścinanie.
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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Chemical, Physical, and Mechanical Properties of 95-Year-Old Concrete Built-In Arch Bridge
PublicationThis research aimed to determine the durability and strength of an old concrete built-in arch bridge based on selected mechanical, physical, and chemical properties of the concrete. The bridge was erected in 1925 and is located in Jagodnik (northern Poland). Cylindrical specimens were taken from the side ribs connected to the top plate using a concrete core borehole diamond drill machine. The properties of the old concrete were...
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Tailoring diamondised nanocarbon-loaded poly(lactic acid) composites for highly electroactive surfaces: extrusion and characterisation of filaments for improved 3D-printed surfaces
PublicationA new 3D-printable composite has been developed dedicated to electroanalytical applications. Two types of diamondised nanocarbons - detonation nanodiamonds (DNDs) and boron-doped carbon nanowalls (BCNWs) - were added as fillers in poly(lactic acid) (PLA)-based composites to extrude 3D filaments. Carbon black served as a primary filler to reach high composite conductivity at low diamondised nanocarbon concentrations (0.01 to 0.2...
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The use of machine learning for face regions detection in thermograms
PublicationThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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FE analysis of support-specimen interaction of compressive experimental test
PublicationThe objective of this work is to investigate the support-specimen interaction during the compressive experimental testing of stiffened plates. The interaction is analyzed employing the nonlinear Finite Element Method using the commercial software ANSYS. The connection between the stiffened plate and testing supports is modelled with the use of contact elements, where several possible interaction scenarios are investigated, and...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning
e-Learning Courses -
The topography of carbon black-polylactide composite 3D printed electrodes after femtosecond laser ablation
Open Research DataThis dataset contains a series of scanning electron microscopy images revealing the topography of 3D printed carbon black-polylactide composite electrodes after laser ablation with a femtosecond laser. Different laser powers were investigated, namely: 10%, 25%, 50%, 75% and 100%. The CB-PLA electrodes were 3D printed using an Ender printer. Femtosecond laser NKT Photonics, Origami XP parameters: power at 100%...
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Model szkolenia "Blended learning" z wykorzystaniem platformy Oracle I-learning.
PublicationW artykule zaproponowano modele organizacyjne szkoleń "blended learning", które pokazują możliwości współpracy firm prywatnych z instytucjami edukacyjnymi w dziedzinie e-learningu. W ramach wspólnego eksperymentu firm Oracle, Incenti S.A., WiedzaNet Sp. z o.o. oraz Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej w semestrze letnim roku akademickiego 2003/2004 udostępniony będzie kurs dla studentów Wydziału Inzynierii Lądowej...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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1D Model Callibration on the Basis on 3D calculations for Tesla Turbine
PublicationThe paper presents the system of equations for axisymmetriclaminar flow, after averaging, through the width of interdisk slit ofTesla turbine. Coefficients were introduced, as a result ofaveraging, that improve the efficiency of 1D model. The minimalnumber of such coefficients was determined. The 1D modelmakes it possible to attain analytical solutions to an accuracylimited by these coefficients. Calibration of 1D model depends...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Calculation of self and mutual inductances of the switched reluctance machine mathematical model.
PublicationA mathematical model of the switched reluctance machine (SRM) in a drive system obtained using Lagrange's energy method and a method of calculation of self and mutual inductances of the SRM are presented in the paper. The self and mutual inductances are elements of Lagrange's function in generalised coordinates and have been calculated using the finite element method (FEM). Selected calculation results for the particular machine...
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Robert Bogdanowicz dr hab. inż.
PeopleRobert Bogdanowicz received his Ph.D. degree with honours in Electronics from the Gdansk University of Technology. He worked as a post-doc researcher in Ernst-Moritz-Arndt-Universität Greifswald Institut für Physik. He has initiated optical emission imaging of muti-magnetron pulsed plasma and contributed to the development of antibacterial implant coatings deposited by high-power impulse magnetron sputtering. He moved back to...
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Comparative study on fracture evolution in steel fibre and bar reinforced concrete beams using acoustic emission and digital image correlation techniques
PublicationIn recent decades, the demand for sustainable construction practices has increased, but raw materials such as reinforcing steel remain scarce. Therefore, steel fibres have emerged as a popular and sustainable choice in the construction industry, offering a cost-effective alternative to traditional steel bar reinforcement for both flatwork and elevated structures. The purpose of this study is therefore to compare the performance...
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Mathematical approach to design 3D scaffolds for the 3D printable bone implant
PublicationThis work demonstrates that an artificial scaffold structure can be designed to exhibit mechanical properties close to the ones of real bone tissue, thus highly reducing the stress-shielding phenomenon. In this study the scan of lumbar vertebra fragment was reproduced to create a numerical 3D model (this model was called the reference bone sample). New nine 3D scaffold samples were designed and their numerical models were created....
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Modelling of reinforced concrete beams under mixed shear-tension failure with different continuous FE approaches
PublicationW artykule omówiono wyniki modelowania numerycznego MES zachowania się wysokich belek żelbetowych podczas zniszczenia mieszanego ścinanie-rozciąganie. Obliczenia wykonano stosując różne modele dla betonu rozszerzone o długość charakterystyczną mikrostruktury w oparciu o teorie nielokalna. Otrzymano dobrą zgodność z wynikami doświadczalnymi.
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SEM micrographs of 3D printed CB-PLA samples topography after microwave treatment
Open Research DataThis dataset contains the SEM micrographs of carbon-black doped polylactic acid 3D printed electrodes, after microwave treatment to activate the electrode surfaces. FEI Quanta 250 FEG SEM was used for these analyses. Samples were treated with CEM reactor or microwave oven.
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Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning
PublicationIn this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...
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Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublicationThe paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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The Effect of Fly Ash Microspheres on the Pore Structure of Concrete
PublicationThe fly ash microspheres (FAMs) formed during the mineral transformation stage in coal combustion are hollow spherical particles with a density less than water. This paper presents the results of X‐ray micro‐computed tomography and an automatic image analysis system of the porosity in the structure of hardened concrete with microspheres. Concrete mixtures with ordinary Portland cement and two substitution rates of cement by microspheres—5%...