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Search results for: E. COLI, MACHINE LEARNING, OPTICAL METHOD, SPECTROSCOPY, URINE, UROSPESIS
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Optical flow method for measuring deformation of soil specimen subjected to torsional shearing
PublicationIn this study optical flow method was used for soil small deformation measurement in laboratory tests. The main objective was to observe how the deformation distributes along the whole height of cylindrical soil specimen subjected to torsional shearing (TS test). The experiments were conducted on dry non-cohesive soil specimens under two values of isotropic pressure. Specimens were loaded with low-amplitude cyclic torque to analyze...
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Extracellular secretion of Pseudoalteromonas sp. cold-adapted esterase in Escherichia coli in the presence of Pseudoalteromonas sp. components of ABC transport system
PublicationEnzymy lipolityczne, głównie lipazy i esterazy, stanowią cenną grupę biokatalizatorów wykorzystywanych w przemyśle. Coraz większe zainteresowanie tą klasą enzymów sprawiło, że poszukuje się alternatywnych źródeł ich pozyskiwania. W celu zbadania wpływu białek transportu ABC Pseudoalteromonas sp. 643A na ekspresję genu, sekrecję i aktywność esterazy EstA z tego mikroorganizmu w systemie ekspresyjnym E. coli skonstruowano układ do...
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Optical Emission Spectroscopy of Microwave (915 MHz) Plasma in Atmospheric Pressure Nitrogen with Addition of Ethanol Vapour
PublicationIn this paper results of optical emission spectroscopic study of microwave 915 MHz plasma in atmospheric pressure nitrogen with an addition of ethanol vapour are presented. The plasma was generated in waveguide- -supplied cylinder-type nozzleless microwave plasma source. The aim of research was to determine the rotational Trot and vibrational Tvib temperatures of CN and C2. A method called bubbling was employed to introduce alcohol (ethanol)...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
PublicationDeep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was...
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Structure and optical parameters of Eu doped tellurium oxide thin films prepared by reactive magnetron sputtering method
PublicationIn this work the structural properties and photoluminescence of tellurium dioxide thin films doped by europium were described. Thin films were deposited by magnetron sputtering method and simultaneously heated at 200 °C. Presence of Eu ions and their valence states was confirmed by X-ray photoemission spectroscopy measurements. The structure of the films as well as the influence of europium dopant on crystalline structure of the...
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A rapid and sensitive method for the quantitative analysis of ibuprofen and its metabolites in equine urine samples by gas chromatography-tandem mass spectrometry
PublicationIbuprofen is widely used in human and veterinary medicine for the treatment of chronic pain as well as rheumatic and musculoskeletal disorders. However, t he anal- gesic and anti-inflammatory properties of Ibuprofen have contributed to frequent drug abuse in equestr ian s ports. A sensitive and rapid gas chromatography with tandem mass spectrometry based method with a simple liquid-liquid extraction and deriva- tization requiring...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublicationPrzedstawiono dydaktyczne modele symulacyjne wykorzystywane w zdalnym kształceniu z zakresu informatyki i technik komunikacyjnych. Pokazano na przykładach zbudowanych symulatorów, w jaki sposób zrealizować lub dostosować modele symulacyjne do zdalnego nauczania. Opisano doświadczenia autorów w wykorzystaniu modeli symulacyjnych w zdalnym nauczaniu.
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New Method of Non-Linear Electrochemical Impedance Spectroscopy with an Amplitude-Modulated Perturbation Signal
PublicationThe paper presents a new method of non-linear electrochemical impedance spectroscopy (NLEIS), which allows fast and nondestructive evaluation of the corrosion rate and determination of the Tafel coefficients values for a corrosion system under investigation. This method employs amplitude modulation of the ac perturbation signal. The study demonstrated that it was possible to obtain impedance characteristic as a function of the...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Dissolution of Nb-doped hydroxyapatite prepared via low-temperature mechanochemical method: Spectroscopy studies
PublicationCalcium phosphate glass ceramics with nominal hydroxyapatite stoichiometry doped with niobium were synthesized using simple as well as low-temperature mechanochemical method and then in the form of compressed pellet were submitted to the static dissolution process in distilled water for one month. The results of structural analysis, performed mainly on the base of spectroscopic methods such as: infrared absorption spectroscopy,...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublicationRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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A facile method for Tauc exponent and corresponding electronic transitions determination in semiconductors directly from UV–Vis spectroscopy data
PublicationIn this work, a facile method allowing for estimation of the exponent in the Tauc equation directly from the UV–vis spectra is presented. It is based on the Taylor expansion of the logarithmic version of the Tauc equation. The Tauc exponent is calculated from the tangent slope of the absorption data. Knowledge of this coefficient provides information about the optical transition types and is used as an input for the calculations...
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Applying of the optical time-of-flight spectroscopy for the paper and pulp characterization
PublicationW pracy przedstawiono korzyści wykorzystania optycznej spektroskopii czasu przelotu w badaniach papieru i miazgi drzewnej. Przedmiotem badań były różne gatunki papieru oraz miazgi drzewnej (bez obróbki cieplnej, po obróbce cieplnej lub po obróbce chemicznej). W pomiarach wykorzystano półprzewodnikowe lasery impulsowe oraz w charakterze fotoodbiorników kamerę smugową lub licznik fotonów.
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Optical time of flight spectroscopy for highly scattering materials measurements.
PublicationW artykule omówiono możliwości wykorzystania optycznej spektroskopii czasu przelotu w wyznaczaniu podstawowych parametrów optycznych materiałów silnie rozpraszających światło. Wykorzystano tu metodę Monte Carlo i metodę dyfuzji.
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Optical-Spectrometry-Based Method for Immunosuppressant Medicine Level Detection in Aqueous Solutions
PublicationIn this paper, an investigation into detecting immunosuppressive medicine in aqueous solutions using a spectrometry-based technique is described. Using optical transmissive spectrometry, absorbance measurements in the spectra range from 250 nm to 1000 nm were carried out for different cyclosporine A (CsA) concentrations in aqueous solutions. The experiment was conducted for samples both with and without interferent substances—glucose...
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Modular machine learning system for training object detection algorithms on a supercomputer
PublicationW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Stacking and rotation-based technique for machine learning classification with data reduction
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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Efficient sampling of high-energy states by machine learning force fields
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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E-learning - prawdziwa czy fikcyjna koncepcja edukacyjnego rozwoju uczelni
PublicationNie można zaprzeczyć, że wykorzystanie narzędzi multimedialnych oraz Internetu pozwala na dodanie istotnych, z punku widzenia dydaktyki, komponentów edukacyjnych tworzących kompetencje i umiejętności zawodowe, a także te czysto akademickie. Trzeba rozważyć, czy wszystkie strony procesu dydaktycznego na uczelni są przygotowane do e−learningu. Oczywistym wymogiem jest posiadanie odpowiedniej bazy sprzętowej i przygotowanej kadry...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Distribution of relaxation times as a method of separation and identification of complex processes measured by impedance spectroscopy
PublicationImpedance spectroscopy is one of the most commonly performed measurements to characterize electronic and electrochemical systems. Impedance spectra have limited resolution and many different processes may overlap what could be the reason of obstructions in its proper later analysis. Up to date, there are three approaches to solve this problem: examining impedance spectra itself, fitting spectra with equivalent circuits, and calculating...
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Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
PublicationDeep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors....
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Estimation of optical parameters of highly scattering materials by time-of-flight spectroscopy.
PublicationPrzedstawiono metody wyznaczania podstawowych parametrów materiałów silnie rozpraszających światło na podstawie pomierzonego rozkładu czasu przelotu krótkich impulsów laserowych. W algorytmie wykorzystano metodę Monte Carlo i metodę dyfuzji do opisu propagacji światła. Oszacowano dokładność oszacowywania tych parametrów.
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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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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Precise Identification of Different Cervical Intraepithelial Neoplasia (CIN) Stages, Using Biomedical Engineering Combined with Data Mining and Machine Learning
PublicationCervical cancer (CC) is one of the most common female cancers worldwide. It remains a significant global health challenge, particularly affecting women in diverse regions. The pivotal role of human papillomavirus (HPV) infection in cervical carcinogenesis underscores the critical importance of diagnostic strategies targeting both HPV infection and cervical...
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THE EFFECT OF WOOD DRYING METHOD ON THE GRANULARITY OF SAWDUST OBTAINED DURING THE SAWING PROCESS USING THE FRAME SAWING MACHINE
PublicationThe experimental results of the study focused on the effect of drying processes of warm air drying at the temperature of 6580°C and warm air-steam mixture drying at the temperature of 105°C of pine and beech wood to the size of sawdust grains created by cutting using RPW 15M frame saw is presented in the paper. Particle size analysis of dry sawdust was performed using two methods - screening method and optical method based on...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Machine Learning and data mining tools applied for databases of low number of records
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublicationBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublicationThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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Determination of API content in a pilot-scale blending by near-infrared spectroscopy as a first step method to process line implementation
PublicationNear infrared (NIR) spectroscopy was used for estimation of powder blend homogeneity and manufacturing control of a medicinal product powder mixture containing active pharmaceutical ingredient (API). Aiming at initiating a Process Analytical Technology (PAT) activity, the first step was a stationary mode atline evaluation. In this, the content of pharmaceutical active compound in the powder mixtures intended to the direct tabletting...
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A high-accuracy method of computation of x-ray waves propagation through an optical system consisting of many lenses
PublicationThe propagation of X-ray waves through an optical system consisting of many X-ray refractive lenses is considered. Two differential equations are contemplated for solving the problem for electromagnetic wave propagation: first – an equation for the electric field, second – an equation derived for a complex phase of an electric field. Both equations are solved by the use of a finite-difference method. The simulation error is estimated...